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Alghoul, Karim. "Heart Rate Variability Extraction from Video Signals." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33003.
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Heart Rate Variability (HRV) analysis has been garnering attention from researchers due to its wide range of applications. Medical researchers have always been interested in Heart Rate (HR) and HRV analysis, but nowadays, investigators from variety of other fields are also probing the subject. For instance, variation in HR and HRV is connected to emotional arousal. Therefore, knowledge from the fields of affective computing and psychology, can be employed to devise machines that understand the emotional states of humans. Recent advancements in non-contact HR and HRV measurement techniques will likely further boost interest in emotional estimation through . Such measurement methods involve the extraction of the photoplethysmography (PPG) signal from the human's face through a camera. The latest approaches apply Independent Component Analysis (ICA) on the color channels of video recordings to extract a PPG signal. Other investigated methods rely on Eulerian Video Magnification (EVM) to detect subtle changes in skin color associated with PPG.
The effectiveness of the EVM in HR estimation has well been established. However, to the best of our knowledge, EVM has not been successfully employed to extract HRV feature from a video of a human face. In contrast, ICA based methods have been successfully used for HRV analysis. As we demonstrate in this thesis, these two approaches for HRV feature extraction are highly sensitive to noise. Hence, when we evaluated them in indoor settings, we obtained mean absolute error in the range of 0.012 and 28.4.
Therefore, in this thesis, we present two approaches to minimize the error rate when estimating physiological measurements from recorded facial videos using a standard camera. In our first approach which is based on the EVM method, we succeeded in extracting HRV measurements but we could not get rid of high frequency noise, which resulted in a high error percentage for the result of the High frequency (HF) component. Our second proposed approach solved this issue by applying ICA on the red, green and blue (RGB) colors channels and we were able to achieve lower error rates and less noisy signal as compared to previous related works. This was done by using a Buterworth filter with the subject's specific HR range as its Cut-Off.
The methods were tested with 12 subjects from the DISCOVER lab at the University of Ottawa, using artificial lights as the only source of illumination. This made it a challenge for us because artificial light produces HF signals which can interfere with the PPG signal. The final results show that our proposed ICA based method has a mean absolute error (MAE) of 0.006, 0.005, 0.34, 0.57 and 0.419 for the mean HR, mean RR, LF, HF and LF/HF respectively. This approach also shows that these physiological parameters are highly correlated with the results taken from the electrocardiography (ECG).
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Soler, Anderson Ivan Rincon. "Impact of artifact correction methods on R-R interbeat signals to quantifying heart rate variability (HRV) according to linear and nonlinear methods." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/59/59135/tde-02052016-130306/.
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In the analysis of heart rate variability (HRV) are used temporal series that contains the distances between successive heartbeats in order to assess autonomic regulation of the cardiovascular system. These series are obtained from the electrocardiogram (ECG) signal analysis, which can be affected by different types of artifacts leading to incorrect interpretations in the analysis of the HRV signals. Classic approach to deal with these artifacts implies the use of correction methods, some of them based on interpolation, substitution or statistical techniques. However, there are few studies that shows the accuracy and performance of these correction methods on real HRV signals. This study aims to determine the performance of some linear and non-linear correction methods on HRV signals with induced artefacts by quantification of its linear and nonlinear HRV parameters. As part of the methodology, ECG signals of rats measured using the technique of telemetry were used to generate real heart rate variability signals without any error. In these series were simulated missing points (beats) in different quantities in order to emulate a real experimental situation as accurately as possible. In order to compare recovering efficiency, deletion (DEL), linear interpolation (LI), cubic spline interpolation (CI), moving average window (MAW) and nonlinear predictive interpolation (NPI) were used as correction methods for the series with induced artifacts. The accuracy of each correction method was known through the results obtained after the measurement of the mean value of the series (AVNN), standard deviation (SDNN), root mean square error of the differences between successive heartbeats (RMSSD), Lomb\'s periodogram (LSP), Detrended Fluctuation Analysis (DFA), multiscale entropy (MSE) and symbolic dynamics (SD) on each HRV signal with and without artifacts. The results show that, at low levels of missing points the performance of all correction techniques are very similar with very close values for each HRV parameter. However, at higher levels of losses only the NPI method allows to obtain HRV parameters with low error values and low quantity of significant differences in comparison to the values calculated for the same signals without the presence of missing points.Na análise da variabilidade da frequência cardíaca (Heart Rate Variability - HRV) são usadas séries temporais que contém as distancias entre batimentos cardíacos sucessivos, com o m de avaliar a regulação autonômica do sistema cardiovascular. Estas séries são obtidas a partir da análise de sinais de eletrocardiograma (ECG), as quais podem ser afetados por distintos tipos de artefatos, levando a interpretações incorretas nas análises feitas sob as séries da HRV. Abordagem clássica para lidar com esses artefatos implica a utilização de métodos de correção, alguns deles com base na interpolação, substituição ou técnicas estatísticas. No entanto, existem poucos estudos que mostram a precisão e desempenho destes métodos de correção em sinais reais da HRV. Assim, o presente estudo tem como objetivo determinar cómo os diferentes níveis de artefatos presentes no sinal afetam as caraterísticas da mesma, utilizando-se diferentes métodos lineares e não lineares de correção e posteriormente quanticação dos parâmetros da HRV. Como parte da metodología utilizada, sinais ECG de ratos obtidas mediante a técnica da telemetria foram usadas para gerar séries de HRV reais sem nenhum tipo de erro. Nestas séries foram simulados batimentos perdidos para diferentes taxas de pontos a m de emular a situação real com a maior precisão possível. Adicionalmente, foram aplicados os métodos de eliminação de segmentos (DEL), interpolação linear (LI) e cúbica (CI), janela de média móvel (MAW) e interpolação preditiva não lineal (NPI) como métodos de correção dos artefatos simulados sob as séries com erros. A precisão de cada método de correção foi conhecida através dos resultados obtidos com a quanticação do valor médio da série (AVNN), desvio padrão (SDNN), erro quadrático médio das diferenças entre batimentos sucessivos (RMSSD), periodograma de Lomb (LSP), análise de flutuações destendenciadas (DFA), entropia multiescala (MSE) e dinâmica simbólica (SD) sob cada sinal de HRV com e sem erros. Os resultados obtidos mostram que para baixos níveis de perdas de batimentos o desempenho das técnicas de correção é similar, com valores muito semelhantes para cada parámetro quanticado da HRV. Não obstante, em níveis de perdas maiores só NPI permite obter valores muito próximos e sem muitas diferenças signicativas para os mesmos parâmetros da HRV, em comparação com os valores calculados para as séries sem perdas.
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Wang, Yuan. "Heart rate variability and respiration signals as late onset sepsis diagnostic tools in neonatal intensive care units." Thesis, Rennes 1, 2013. http://www.theses.fr/2013REN1S106/document.
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Le sepsis tardif, défini comme une infection systémique chez les nouveaux nés âgés de plus de 3 jours, survient chez environ 7% à 10% de tous les nouveau-nés et chez plus de 25% des nouveau-nés de très faible poids de naissance qui sont hospitalisés dans les unités de soins intensifs néonatals (USIN). Les apnées et bradycardies (AB) spontanées récurrentes et graves sont parmi les principaux indicateurs précoces cliniques de l'infection systémique chez les prématurés. L'objectif de cette thèse est de déterminer si la variabilité du rythme cardiaque (VRC), la respiration et l'analyse de leurs relations aident au diagnostic de l'infection chez les nouveaux nés prématurés par des moyens non invasifs en USIN. Par conséquent, on a effectué l'analyse Mono-Voie (MV) et Bi-Voies (BV) sur deux groupes sélectionnés de nouveau-nés prématurés: sepsis (S) vs. non-sepsis (NS). (1) Tout d'abord, on a étudié la série RR non seulement par des méthodes de distribution (moy, varn, skew, kurt, med, SpAs), par les méthodes linéaire: le domaine temporel (SD, RMSSD) et dans le domaine fréquentiel (p_VLF, p_LF, p_HF), mais aussi par les méthodes non–linéaires: la théorie du chaos (alphas, alphaF) et la théorie de l'information (AppEn, SamEn, PermEn, Regul). Pour chaque méthode, nous étudions trois tailles de fenêtre 1024/2048/4096, puis nous comparons ces méthodes afin de trouver les meilleures façons de distinguer S de NS. Les résultats montrent que les indices alphaS, alphaF et SamEn sont les paramètres optimaux pour séparer les deux populations. (2) Ensuite, la question du couplage fonctionnel entre la VRC et la respiration nasale est adressée. Des relations linéaires et non-linéaires ont été explorées. Les indices linéaires sont la corrélation (r²), l'indice de la fonction de cohérence (Cohere) et la corrélation temps-fréquence (r2t,f) , tandis que le coefficient de régression non-linéaire (h²) a été utilisé pour analyser des relations non-linéaires. Nous avons calculé les deux directions de couplage pendant l'évaluation de l'indice h2 de régression non-linéaire. Enfin, à partir de l'ensemble du processus d'analyse, il est évident que les trois indices (r2tf_rn_raw_0p2_0p4, h2_rn_raw et h2_nr_raw) sont des moyens complémentaires pour le diagnostic du sepsis de façon non-invasive chez ces patients fragiles. (3) Après, l'étude de faisabilité de la détection du sepsis en USIN est réalisée sur la base des paramètres retenus lors des études MV et BV. Nous avons montré que le test proposé, basé sur la fusion optimale des six indices ci-dessus, conduit à de bonnes performances statistiques. En conclusion, les mesures choisies lors de l'analyse des signaux en MV et BV ont une bonne répétabilité et permettent de mettre en place un test en vue du diagnostic non invasif et précoce du sepsis. Le test proposé peut être utilisé pour fournir une alarme fiable lors de la survenue d'un épisode d'AB tout en exploitant les systèmes de monitoring actuels en USINLate-onset sepsis, defined as a systemic infection in neonates older than 3 days, occurs in approximately 10% of all neonates and in more than 25% of very low birth weight infants who are hospitalized in Neonatal Intensive Care Units (NICU). Recurrent and severe spontaneous apneas and bradycardias (AB) is one of the major clinical early indicators of systemic infection in the premature infant. Various hematological and biochemical markers have been evaluated for this indication but they are invasive procedures that cannot be repeated several times. The objective of this Ph.D dissertation was to determine if heart rate variability (HRV), respiration and the analysis of their relationships help to the diagnosis of infection in premature infants via non-invasive ways in NICU. Therefore, we carried out Mono-Channel (MC) and Bi-Channel (BC) Analysis in two selected groups of premature infants: sepsis (S) vs. non-sepsis (NS). (1) Firstly, we studied the RR series not only by distribution methods (moy, varn, skew, kurt, med, SpAs), by linear methods: time domain (SD, RMSSD) and frequency domain (p_VLF, p_LF, p_HF), but also by non-linear methods: chaos theory (alphaS, alphaF) and information theory (AppEn, SamEn, PermEn, Regul). For each method, we attempt three sizes of window 1024/2048/4096, and then compare these methods in order to find the optimal ways to distinguish S from NS. The results show that alphaS, alphaF and SamEn are optimal parameters to recognize sepsis from the diagnosis of late neonatal infection in premature infants with unusual and recurrent AB. (2) The question about the functional coupling of HRV and nasal respiration is addressed. Linear and non-linear relationships have been explored. Linear indexes were correlation (r²), coherence function (Cohere) and time-frequency index (r2t,f), while a non-linear regression coefficient (h²) was used to analyze non-linear relationships. We calculated two directions during evaluate the index h2 of non-linear regression. Finally, from the entire analysis process, it is obvious that the three indexes (r2tf_rn_raw_0p2_0p4, h2_rn_raw and h2_nr_raw) were complementary ways to diagnosticate sepsis in a non-invasive way, in such delicate patients.(3) Furthermore, feasibility study is carried out on the candidate parameters selected from MC and BC respectively. We discovered that the proposed test based on optimal fusion of 6 features shows good performance with the largest Area Under Curves (AUC) and the least Probability of False Alarm (PFA). As a conclusion, we believe that the selected measures from MC and BC signal analysis have a good repeatability and accuracy to test for the diagnosis of sepsis via non-invasive NICU monitoring system, which can reliably confirm or refute the diagnosis of infection at an early stage
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Franěk, Pavel. "Analýza variability srdečního rytmu pomocí rekurentního diagramu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220048.
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The aim of this thesis is to describe the variability of cardiac rhythm and familiarity with the methods of the analysis, ie by monitoring changes in heart rhythm electrogram signal recording and using the methods in the time domain using recurrent diagram. The work describes the quantification of the methods and possibilities of quantifiers in the evaluation of heart rate variability analysis. It also describes the clinical significance of heart rate variability and diagnostic capabilities changes of heart rate variability caused by ischemic heart disease. The practical part describes how to create applications in Matlab to calculate the quantifiers analysis of heart rate variability in the time domain using recurrent diagram. The calculation was made of the positions R wave elektrogram signal isolated rabbit hearts. The calculated values of quantifiers both methods were statistically evaluated and discussed.
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Johnston, William S. "Development of a signal processing library for extraction of SpO2, HR, HRV, and RR from photoplethysmographic waveforms." Worcester, Mass. Worcester Polytechnic Institute, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-073106-130906/.
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Thesis (M.S.)--Worcester Polytechnic Institute.Keywords: wearable medical sensors; arterial oxygen saturation; software development; embedded systems; heart rate; respiration rate; heart rate variability; pulse oximetry; digital signal processing Includes bibliographical references (leaves 125-133).
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Jež, Radek. "Software pro ruční rozměření signálů EKG." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-219251.
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This thesis deals with evaluation EKG in terms of classification rhythm and analysis HRV. In theoretic part of work are described basics of heart physiology and its usual pathology, basics of electrocardiography, evaluation EKG and standard methods of HRV evaluation. In practical part are described algorithms used in created application. Mainly describes technique of rhythm evaluation, ectopic rhythms and delineation error elimination, data preparing for HRV evaluation, drift removal from DES and HRV evaluation methods. Created program was tested on CSE and MIT- BIH database records. For lack of suitable data and absence of tested data, it wasn’t possible to test all the classification rules of used algorithms. Tested part of program appears reliable and functional.
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Heathers, James. "Methodological improvements in heart rate variability." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/13106.
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Heart rate variability (HRV) refers to the amplitude and period of fluctuations in the heart rate over time. HRV is an accessible, low-cost and straightforward technique for measuring autonomic outflow, but also a complicated epiphenomena of interacting autonomic, circulatory and respiratory factors. Confusion about the meaning of HRV is reflected in the literature establishing basic HRV theory, and in the applied literature which uses HRV as a dependent variable or predictor of psychological outcomes. Here, 2 straightforward issues present themselves: 1) best-case practice for methodological implementation is not being followed, and 2) sample sizes for between-subjects investigations of phenomena where HRV is a dependent variable are underpowered. Specifically addressing the above; 1) an attempt is made to a) understand and codify a best-case practice for methodological control in biobehavioural research, and b) investigate profound but common sources of error in HRV recording; 2) rationale for the development and field testing of a device which allows mass collection of HRV records from experimental participants is outlined. Best-case practice for experimental implementation is recommended: the use of within-subjects data, the consideration of the nature of ‘baseline’ periods against which experimental conditions are compared, and respiratory monitoring within participants to control for occasional or whole-sample artifacts. Current research is not well controlled – theoretical, statistical and practical errors are widely observed. For addressing experimental power, pulse monitoring shows acceptable reliability over time, and the device developed (a smartphone-based pulse rate monitor) shows excellent accuracy in comparison to conventional measurement. A novel solution for correcting pulse to pulse intervals is offered which improves measurement accuracy and performs well in field trials of mass-collected data.
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Boman, Kajsa. "Heart rate variability : A possible measure of subjective wellbeing?" Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15911.
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Wellbeing and subjective wellbeing (SWB) has become some the most important goals of our time, both individually and societally. Thus, there is a need for reliable ways to measure SWB, as concerns regarding many current measures have been raised. Due to the interwoven nature of physiology and psychology, heart rate variability (HRV) has the potential to assess psychological processes in a physiological manner. HRV is an attractive measure since it is inexpensive, easy and non-invasive. Hence, the aim is to, from a cognitive neuroscientific standpoint, investigate whether HRV could serve as an objective measure to assess SWB. Most studies demonstrate associations between HRV and SWB, in particular between high frequency (HF)-HRV and positive affect (PA). However, the one study fully matching the theoretical framework only showed an inverse correlation between HRV and negative affect (NA). Plausibly implying that HRV does not serve as a reliable measure of SWB, but may be able to indicate inverse associations with NA, and possibly index certain aspect of SWB such as deactivated PA. The study of the relationship between HRV and SWB is still in its infancy and results are inconsistent. The lack of common standards regarding measurements, implementation details, and variable values, make results difficult to compare and generalize. Further standardizations and research are much needed before accurate conclusions can be drawn.
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Suh, Sooyeon. "STRESS, ANXIETY, AND HEART RATE VARIABILITY IN CHRONIC OBSTRUCTIVE PULMONARY DISEASE." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275495558.
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Minnis, James Michael. "Nutrition and athletic performance: implications of heart rate variability." Kansas State University, 2015. http://hdl.handle.net/2097/20344.
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Master of ScienceDepartment of Human Nutrition
Mark Haub
The purpose of this review is to examine the role of heart rate variability (HRV) as a predictor of athletic readiness and performance and assess whether nutrition strategies can be implemented to create favorable HRV indices with the goal of improving athletic readiness and performance. The balance between training and recovery is crucial for reaching an optimal adaptation and avoiding overtraining, allowing for improved readiness to train and compete. The measurement of HRV is non-invasive and is used primarily to quantify physical and mental stress in athletes by monitoring the effects of the autonomic nervous system on the heart. Current data suggests a relationship between resting parasympathetic tone, via time and frequency domains, and athletic performance. Parasympathetic modulated HRV indices have been associated with performance metrics such as peripheral work capacity, aerobic power, running and sprint performance, swimming performance, weight lifting performance, anaerobic capacity, strength, and enhanced mental focus/skill execution. The use of nutrition to help enhance sports performance is becoming more common. Evidence-based sports nutrition provides fuel for training/competition, assists in maximizing training adaptations, enhances recovery, improves mental focus, and aids in injury prevention and recovery. The use of nutrition strategies to influence HRV is novel and current evidence is scarce in regards to nutritional effects on HRV, specifically in athletes. Current research suggests that achieving energy balance and decreasing body fat in overweight/obese individuals has positive effects on the vagal component of HRV indices. Proper hydration, fruit and vegetable intake, a moderate carbohydrate diet, omega-3 fatty acid supplementation/intake also seem to have positive effects on HRV indices. Certain individual supplements have been studied in regards to HRV including casein hydrolysate, amaranth oil, and bovine colostrum. Caffeine seems to have the opposite effect on HRV indices, increasing sympathetic modulation while decreasing parasympathetic modulation. Much more research needs to be done in regard to potential nutritional influences on HRV so that sport dietitians feel confident in the methods currently used to assess athlete readiness and determining what types of nutrition strategies may be used to further improve the performance of an athlete.
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Free, Matthew Lee. "Heart Rate Variability at Rest and During Worry in Chronic Worriers." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555597778352683.
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Ledoux, Thomas M. "The Role of Heart Rate Variability in the Treatment of Migraines." Antioch University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1427823107.
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Joseph, Nicholas Patrick Joseph. "An Examination of the Association between Heart Rate Variability, Anxiety, and The Need for Affect." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1537810169788763.
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Shafer, Lauren Marie. "Low-Impact Yoga Improves Flexibility, but Has No Effect on Heart Rate Variability in Sedentary Adult Women." Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1535410337213529.
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Caha, Martin. "Klasifikace EKG na základě metod HRV analýzy." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220051.
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This paper deals with the classification of ECG measured from isolated rabbit hearts during the experiment with repeated ischemia. Classification features were calculated using the methods of heart rate variability analysis. The results were statistically evaluated. Heart rate variability parameters were calculated using Kubios HRV, other calculations were performed in MATLAB. Artificial neural network was created to classify the analyzed parameters to specific groups.
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Langlois, Carolyn M. "Levels of Emotional Awareness: A psychophysiological investigation." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1253561949.
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Hu, Dixie Doreen. "Forgiveness from the Heart: A Psychophysiological Study." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1471276252.
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Madison, Annelise Alissa. "Social Anxiety Symptoms, Heart Rate Variability, and Vocal Emotion Recognition: Evidence of a Normative Vagally-Mediated Positivity Bias in Women." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu15582676377176.
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Ellis, Robert J. "The effect of musical tempo on subjective and physiological indices of affective response." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250634561.
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Piedmont, Joanna I. "Examining Generalized Anxiety Disorder During Social Interactions: Cardiac Activity, and the Influence of Affect." University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1449839541.
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Speller, Lassiter F. "The Effects of Training and Individual Differences in Heart Rate Variability on the Golf Swing’s Coordination Structure." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345224279.
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Číhal, Martin. "Analýza variability srdečního rytmu pomocí fraktální dimenze." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220052.
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This work is focused on fractal dimension utilization for heart rate variability analysis. Both the theory of heart rate variability and the methods of HRV analysis in time domain and using the fractal dimesion are summarized. Short comparsion of time domain and fractal dimension method is presented.
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Spielmann, Nadine. "Heart rate variability in relation to the menstrual cycle in trained and untrained women." Doctoral thesis, Humboldt-Universität zu Berlin, Philosophische Fakultät IV, 2005. http://dx.doi.org/10.18452/15169.
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Einleitung: Es wird angenommen, dass die zyklusbedingten, hormonellen Änderungen die vegetative Ansteuerung des Herzens bei normotensiven Frauen beeinflussen. Die Herzfrequenzvariabilität (HRV) stellt einen der am häufigsten untersuchten, nicht-invasiven Parameter des Herz-Kreislauf-Systems dar. Deshalb war es das Ziel dieser Studie, den Verlauf der HRV Parameter bei ausdauertrainierten als auch untrainierten normotensiven Frauen in Abhängigkeit vom Menstruationszyklus zu untersuchen. Methode: Normotensive, untrainierte als auch trainierte Frauen nahmen an der Studie teil. Die Athletinnen absolvierten individuell abgestimmte Trainingspläne (>5h/Woche) während der Studie. Die HRV Messungen wurden in den folgenden fünf Zyklusphasen aufgezeichnet: In der Menstruation (M), der Mitte der Follikel- (MidF), der Ovulations- (O), der Mitte der Luteal- (MidL) und der Pre-Menstruationsphase (PreM). Die Basaltemperatur als auch die Hormonanalysen des Luteinisierenden (LH) und des Follikelstimulierenden Hormons (FSH), des β-17 Östrogens (E2) und des Progesterons (P) dienten der Verifizierung der Zyklusphasen. Die HRV Messungen wurden bei Spontanatmung im Liegen (20 min) wie auch während eines Orthosthase Tests aufgezeichnet. Parameter der Zeit als auch der Frequenzdomäne für Kurzzeitmessungen wurden ausgewertet. Resultate: Alle Frauen hatten einen normotensiven Menstruationszyklus mit typischen hormonellen Schwankungen und einem signifikanten Verlauf (pIntroduction: The autonomic control of the heart is assumed to be affected by endogenous hormonal fluctuations in normal ovulatory females. Analyzing heart rate variability (HRV) had become a tool for the noninvasive measurement of cardiac autonomic control. The purpose of the present study was to investigate the course of the HRV parameters in moderately active as well as in long time endurance trained women during the menstrual cycle. Methods: Normal ovulatory females, untrained and trained were enrolled. Female athletes were involved in individually different training patterns (>5h/week) during the study. HRV recordings were obtained during five different menstrual cycle phases: menstruation (M), middle of follicular (MidF), ovulation (O), middle of luteal (MidL) and pre menstruation phase (PreM). Phases were verified by basal body temperature and analysis of luteinizing hormone (LH), follicular stimulation hormone (FSH), β-17 estrogen (E2) and progesterone (P). HRV measurements took place at subjects’ spontaneous breathing frequency in supine position (20 min) as well as during an orthostatic test. Parameters of short-term recording were calculated in time and frequency domain. Results: All women had normal ovulatory menstrual cycles including typical endogenous hormonal fluctuations; levels of LH, FSH, E2 and P were significantly different (p
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Čukić, Iva. "Personality traits and health outcomes : an exploration into associations and potential mechanisms." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/16170.
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There were two main objectives of this thesis. First, given that personality traits have been linked to a number of diabetes risk factors and precursors such as lifestyle and the metabolic syndrome, our aim is to explore whether personality traits are associated with type 1 and type 2 diabetes mellitus. Second, we aim to investigate several potential mechanisms by which personality could influence diabetes, and other health outcomes such as cardiovascular disease and mortality. Chapter 1 provides an introductory overview of the history of personality-health research, and discusses strengths and limitations of different methodological frameworks. Chapters 2-4 focus on the associations between personality and diabetes. Two studies described in Chapter 2 examine cross-sectional and longitudinal associations between personality and type 1 and type 2 diabetes. We used a large national sample with ten years of follow-up. We detected positive associations between openness and neuroticism and type 1 diabetes prevalence, and negative associations between neuroticism and type 2 diabetes incidence. In Chapter 3, we examine relationships between personality and type 2 diabetes incidence using aggregated personality and diabetes data on a level of the U.S. counties and states. In a six-years follow-up study, we found no evidence that mean levels of personality traits were associated with diabetes incidence in the U.S. states. In the following chapter we explore whether a possible mechanism by which personality may influence diabetes is by moderating the expression of its genetic risk. The study described in Chapter 4 looks at interactions between personality domains and facets with polygenic risk score for type 2 diabetes in predicting glycated haemoglobin levels using a large community-dwelling sample. This study found a negative phenotypic correlation between openness and glycated haemoglobin levels, though this association was confounded by cognitive ability. Moreover, genetic risk for diabetes was more strongly associated with glycated haemoglobin levels in people with lower levels of either agreeableness or conscientiousness. In Chapter 5 we move away from diabetes to discuss previously reported contradictory results regarding the effects neuroticism has on mortality. Some of the previous studies reported higher neuroticism being associated with higher risk of mortality, whereas some reported that higher neuroticism was associated with lower risk of death. We tested whether the sign of the neuroticism effect was a function of the covariates included in the models. In a national sample with ten years of follow-up we found that neuroticism was a risk factor for death in the models that did not include objective and self-rated health variables. However, when these variables were included, neuroticism was related to lower risk of death. In the last empirical chapter, Chapter 6, we explore whether autonomic nervous system activity is a biomarker for personality traits. The first study tests whether openness is associated with measures of sympathetic and parasympathetic nervous system activation. We find that openness was associated with sympathetic nervous system activity under baseline but not in the stress conditions, and that it was not associated with measures of parasympathetic activation. The second study describes a model of associations between neuroticism and autonomic nervous system activation, while controlling for cardiovascular disease and depression and their mutual associations. We found that neuroticism has independent contributions to all measures of autonomic nervous system activity, and to heart disease, even when controlling for relevant clinical variables. Thus, autonomic nervous system activity may explain in part observed links between personality, and heart disease and mortality. Finally, in Chapter 7 we summarize the findings presented in the five empirical chapters, discuss the limitations of the current method, and offer suggestions for future research in the field.
25
Herbell, Kayla. "Social Determinants of Health and Psychophysiological Stress in Pregnant Women: Correlates with Maternal Mental Health." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1534160752855093.
Full text
26
Zaturenskaya, Mariya. "The Role of Mindfulness in Cardiovascular Recovery from Stress." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1563462730045067.
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27
Vykoupil, Pavel. "Použití analýzy HRV pro automatickou detekci ischemie u izolovaného zvířecího srdce." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220564.
Full textAbstract:
This paper deals with HRV analysis, creating segments for this analysis, calculating HRV parameters and their classification for automatic detection of ischemia. First part of the work is dedicated to theoretical describtion of heart anatomy, ECG reading, its processing and methods of HRV analysis. Next part of this work outline the principle of creating segments used for calculation of HRV parameters. Last part of the work indtroduces classification of said parameters with the help of multilayered neural networks and finding their best possible setup based on least classification error and computing time achieved. Calculation of HRV parameters and classification was realized using software Matlab.
28
Penzlin, Ana Isabel, Kristian Barlinn, Ben Min-Woo Illigens, Kerstin Weidner, Martin Siepmann, and Timo Siepmann. "Effect of short-term heart rate variability biofeedback on long-term abstinence in alcohol dependent patients – a one-year follow-up." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-230932.
Full textAbstract:
Background:
A randomized controlled study (RCT) recently showed that short-term heart rate variability (HRV) biofeedback in addition to standard rehabilitation care for alcohol dependence can reduce craving, anxiety and improve cardiovascular autonomic function. In this one-year follow-up study we aimed to explore whether completion of 2-week HRV-Biofeedback training is associated with long-term abstinence. Furthermore, we sought to identify potential predictors of post-treatment abstinence.
Methods:
We conducted a survey on abstinence in patients with alcohol dependence 1 year after completion of an RCT comparing HRV-biofeedback in addition to inpatient rehabilitation treatment alone (controls). Abstinence rates were compared and analysed for association with demographic data as well as psychometric and autonomic cardiac assessment before and after completion of the biofeedback training using bivariate and multivariate regression analyses.
Results:
Out of 48 patients who participated in the RCT, 27 patients (9 females, ages 42.9 ± 8.6, mean ± SD) completed our one-year follow-up. When including in the analysis only patients who completed follow-up, the rate of abstinence tended to be higher in patients who underwent HRV-biofeedback 1 year earlier compared to those who received rehabilitative treatment alone (66.7% vs 50%, p = ns). This non-significant trend was also observed in the intention-to-treat analysis where patients who did not participate in the follow-up were assumed to have relapsed (46,7% biofeedback vs. 33.3% controls, p = ns). Neither cardiac autonomic function nor psychometric variables were associated with abstinence 1 year after HRV-biofeedback.
Conclusion:
Our follow-up study provide a first indication of possible increase in long-term abstinence after HRVbiofeedback for alcohol dependence in addition to rehabilitation.
Trial registration: The original randomized controlled trial was registered in the German Clinical Trials Register (DRKS00004618). This one-year follow-up survey has not been registered.
29
Huang, Lin. "Effects of aromatherapy on negative emotions and work and study performance: heart rate variability analysis to assess the balance of the autonomic nervous system." Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/402260.
Full textAbstract:
El
objetivo
general
de
esta
tesis
es
analizar
la
eficacia
de
la
aromaterapia
(AR)
para
reducir
las
emociones
negativas
e
incrementar
el
nivel
de
atención
y
rendimiento
en
el
situaciones
laborales
y
académicas.
Se
probará
esta
eficacia
con
cuestionarios
y
evaluando
el
equilibrio
del
Sistema
Nervioso
Autónomo
a
partir
del
análisis
HRV.
Para
llevar
a
cabo
este
objetivo
general,
se
realizarán
dos
estudios
principales.
Analizaremos
los
efectos
de
la
AR
sobre
la
variabilidad
de
la
frecuencia
cardíaca
(HRV)
como
un
marcador
del
equilibrio
simpático/parasimpático
desde
el
SNA.
El
objetivo
para
el
Estudio
1
fue
analizar
la
eficacia
de
la
AR
parea
reducir
la
ansiedad
y
mejorar
la
concentración
en
el
estudio
en
estudiantes
universitarios.
La
muestra
fue
de
12
estudiantes
(edad
entre
18
y
33
años).
Analizamos
los
efectos
del
aceite
esencial
de
albahaca
(Basil)
a
corto
término
(1
hora)
y
a
largo
término
(1
mes).
Encontramos
que
la
inhalación
del
aceite
esencial
de
albahaca
reduce
las
puntuaciones
de
ansiedad
y
mejora
la
variabilidad
cardíaca
(parámetros
SDRR
y
RMSSD).
La
AR
en
una
sesión
corta
o
con
una
botella
aromática
colgada
del
cuello
cada
día
durante
un
mes
produce
cambios
emocionales
y
de
HRV
en
los
participantes.
El
objetivo
del
Estudio
2
fue
analizar
la
eficacia
de
la
AR
para
mejorar
el
rendimiento
laboral
y
reducir
el
estrés
en
el
lugar
de
trabajo.
La
muestra
estaba
formada
por
42
trabajadores
universitarios
administrativos
(edad:
42.21
años,
SD=7.12;
género:
10
hombres
y
32
mujeres).
Todas
las
sesiones
fueron
realizadas
en
un
aula
universitaria
de
ordenadores
personales.
Los
participantes
fueron
asignados
al
azar
a
un
grupo
de
aromaterapia
(AG)
y
a
un
grupo
control
(CG),
y
fueron
invitados
a
participar
en
una
sesión
específica
solo
una
vez.
Se
sentaron
frente
a
un
ordenador.
Durante el período de intervención, se pusieron en marcha algunos
difusores de aceite y se mantuvieron funcionando a lo largo de la sesión con
aceite esencial de petit grain para las sesiones del grupo AG y un aceite
neutro (almendra) para las sesiones de CG. Al mismo tiempo, los
participantes completaron una tarea de ordenador en un sitio web específico
escribiendo con su teclado hasta que la terminaron. Los tiempos fueron
diferentes para todos los participantes y se registraron en el sitio web como
"Tiempo de ejecución". El grupo de aromaterapia realizó la tarea del sitio web
con el teclado 2, 28 min más rápido que la de CG (p = 0,05) y mostró una
mejor variabilidad cardíaca (parámetros HF, SDNN y RMSSD). La inhalación
de aceite esencial Petitgrain reduce el estrés y mejora el rendimiento en el
lugar de trabajo. La AR mejora el tiempo de rendimiento al escribir con el
teclado en una sesión simulada de trabajo de ordenador y produce algunos
cambios mejorando la HRV.
Conclusiones generales: Esta tesis doctoral confirma que la aromaterapia
(inhalar aceites esenciales) puede mejorar el rendimiento en el lugar de
trabajo, puede ayudar a manejar emociones negativas y puede incrementar el
nivel de atención en situaciones académicas y laborales. Nuestros resultados
confirman que la inhalación de aceites esenciales produce este efecto
equilibrando el sistema simpático / parasimpático del Sistema Nervioso
Autonómo. El análisis de HRV es un buen marcador de este efecto. Este
equilibrio del SNA puede explicarse por una acción combinada de los
componentes principales de los aceites esenciales Petitgrain y Basil. Algunos
de ellos tienen efectos sedantes, que pueden inducir cambios en la actividad
parasimpática, y otros componentes tienen efectos de activación, que
estimulan la actividad simpática. El efecto final puede ser una mejora de la
condición mental y emocional por una combinación de reducir el nivel de
estrés y aumentar el nivel de arousal de los participantes en términos de
atención y alerta. También podemos explicar nuestros resultados según la
Medicina Tradicional China (TCM). Los aceites esenciales pueden trabajar a
través de una terapia verdaderamente holística, teniendo en cuenta la mente,
el cuerpo y el espíritu de la persona. Los aceites esenciales pueden
conectarse con nuestro cuerpo y ayudarlo a encontrar la mejor manera de
resolver sus necesidades. Los efectos relajantes (actividad parasimpática)
pueden estar relacionados con el YIN y los efectos de activación (actividad
simpática) pueden estar relacionados con el YANG.The general aim of this thesis is to analyse the aromatherapy (AR) efficacy to reduce negative emotions and increase the attention level and performance in the workplace and in academic situations. Its efficacy will be tested through questionnaires and by checking the balance of the Autonomic Nervous System through HRV analysis. To carry out this general objective, we conducted two main studies. We will analyse the AR effects over the heart rate variability (HRV) as a marker of the sympathetic/parasympathetic balance from the ANS. The objective for Study 1 was to analyse the AR efficacy for reducing anxiety and improving study concentration in university students. The sample was composed by 12 students (age between 18 and 33 years old). We analysed the effects of basil essential oil inhalation at short-‐time (1 hour) and at long-‐time (1 month). We found that Inhalation of Basil essential oil reduces anxiety scoring and improves cardiac variability (SDRR and RMSSD parameters). AR in a short session or with an aromatic necklace every day during one month produces emotional and HRV changes on participants. The objective for Study 2 was to analyse the aromatherapy efficacy to improve the work performance and reduce the workplace stress. The sample was composed by 42 administrative university workers (age: 42.21 years, SD=7.12; gender: 10 men and 32 women). All sessions were performed in a university computer classroom. The participants were randomly assigned into an aromatherapy group (AG) and a control group (CG), and they were invited to participate in a specific session only once. They were seated in front of a computer. During the intervention period, some oil diffusers were launched and worked throughout the session with petit grain essential oil for AG sessions and a neutral oil (almond) for CG sessions. At the same time, participants completed a computer task in a specific website typing on their keyboard until they finished it. The single times were different for all participants and were recorded in the website as “Performance Time”. The aromatherapy group performed the website task with the keyboard 2, 28 min faster than CG typing (p=0.05) and showed better cardiac variability (HF, SDNN and RMSSD parameters). Inhalation of Petitgrain essential oil reduces stress and improves performance in the workplace. AR improves the performance time when typing with the keyboard in a simulated computer work session and produces some changes improving HRV. General Conclusions: This doctoral thesis confirms that aromatherapy (inhaling essential oils) can improve performance in the workplace, can help to manage negative emotions and can increment attention level in academic and workplace situations. Our results confirm that inhalation of essential oils produces this effect by balancing the sympathetic/parasympathetic system of the Autonomic Nervous System. HRV analysis is a good marker of this effect. This ANS balance can be explained by a combined action of the Petitgrain and Basil main components. Some of them have sedative effects, which can induce changes on the parasympathetic activity, and other components have activation effects, which stimulate the sympathetic activity. The final effect can be an improvement of the mental and emotional condition by a combination of reducing stress level and increasing arousal level of the participants in terms of attentiveness and alertness. We can also explain our results according to TCM. Essential oils can work through a truly holistic therapy, taking into account the mind, the body and the spirit of the person. Essential oils can connect with our body and help it to find the best way to solve its needs. The relaxing effects (parasympathetic activity) can be related to YIN and the activation effects (sympathetic activity) can be related to YANG.
30
Nytorpe, Piledahl Staffan, and Daniel Dahlberg. "Detektering av stress från biometrisk data i realtid." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-31248.
Full textAbstract:
At the time of writing, stress and stress related disease have become the most common reasons for absence in the workplace in Sweden. The purpose of the work presented here is to identify and notify people managing unhealthy levels of stress. Since symptoms of mental stress manifest through functions of the Sympathetic Nervous System (SNS), they are best measured through monitoring of SNS changes and phenomena. In this study, changes in the sympathetic control of heart rate were recorded and analyzed using heart rate variability analysis and a simple runner’s heart rate sensor connected to a smartphone. Mental stress data was collected through stressful video gaming. This was compared to data from non-stressful activities, physical activity and extremely stressful activities such as public speaking events. By using the period between heartbeats and selecting features from the frequency domain, a simple machine learning algorithm could differentiate between the types of data and thus could effectively recognize mental stress. The study resulted in a collection of 100 data points, an algorithm to extract features and an application to continuously collect and classify sequences of heart periods. It also revealed an interesting relationship in the data between different subjects. The fact that continuous stress monitoring can be achieved using minimally intrusive sensors is the greatest benefit of these results, especially when connsidering its potential value in the identification and prevention of stress related disease.
31
Johansson, Amanda. "Idiopathic environmental intolerance attributed to electromagnetic fields : physiological and psychological aspects." Doctoral thesis, Umeå universitet, Yrkes- och miljömedicin, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1886.
Full textAbstract:
This thesis aims to increase the knowledge on people with symptoms attributed to electromagnetic fields (EMF) by investigating the effects of EMF exposure and by additional description of the heterogeneous group of people reporting EMF-related symptoms. The effect of mobile phone (MP)-like radio frequency (RF) fields on symptoms, autonomic nervous system (ANS) parameters, short-term memory, and reaction time in persons with MP-related symptoms (MP participants) was investigated in a provocation study. A second provocation study investigated the effect of similar exposure on serum concentration of biomarkers in persons with atopic dermatitis. No effect of exposure was detected in either study. MP participants displayed changes in heart rate variability (HRV) during cognitive tests, but not during rest. This contrasts with earlier findings, participants with symptoms attributed to EMF sources in general (EHS participants) displayed an elevated sympathetic nervous system activity both during cognitive tests and during rest. Proposed differences between subgroups of persons with EMF-related symptoms with respect to symptoms, personality traits and stress were investigated in a questionnaire study. MP participants reported primarily symptoms from the head; EHS participants reported symptoms from many organ systems. Furthermore, EHS participants reported higher levels of anxiety, depression, stress, and exhaustion when compared with a reference group. MP participants reported higher levels of anxiety and exhaustion only. In a pilot study, 24-hour and short-term HRV were investigated in EHS participants, to examine whether the previously observed sympathovagal imbalance would still be present. There was a tendency toward increased parasympathetic activity compared with earlier recordings, and a reduction of symptoms. Twenty-four hour and short-term recordings were fairly similar for each participant; however, there were large between-subject differences. The results do not support the hypothesis of effects of MP-like RF exposure on symptoms, ANS activity, CFFT, cognitive function, or biomarkers. However, they do support the hypothesis that persons with different symptom attribution (MP and EHS) may differ also in ANS activity and psychological aspects.
32
Padin, Avelina C. "Implicit attitudes, physical activity and self-regulatory capacity." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1467813684.
Full text
33
Shi, Ping. "Photoplethysmography in noninvasive cardiovascular assessment." Thesis, Loughborough University, 2009. https://dspace.lboro.ac.uk/2134/5399.
Full textAbstract:
The electro-optic technique of measuring the cardiovascular pulse wave known as photoplethysmography (PPG) is clinically utilised for noninvasive characterisation of physiological components by dynamic monitoring of tissue optical absorption. There has been a resurgence of interest in this technique in recent years, driven by the demand for a low cost, compact, simple and portable technology for primary care and community-based clinical settings, and the advancement of computer-based pulse wave analysis techniques. PPG signal provides a means of determining cardiovascular properties during the cardiac cycle and changes with ageing and disease. This thesis focuses on the photoplethysmographic signal for cardiovascular assessment. The contour of the PPG pulse wave is influenced by vascular ageing. Contour analysis of the PPG pulse wave provides a rapid means of assessing vascular tone and arterial stiffness. In this thesis, the parameters extracted from the PPG pulse wave are examined in young adults. The results indicate that the contour parameters of the PPG pulse wave could provide a simple and noninvasive means to study the characteristic change relating to arterial stiffness. The pulsatile component of the PPG signal is due to the pumping action of the heart, and thus could reveal the circulation changes of a specific vascular bed. Heart rate variability (HRV) represents one of the most promising quantitative markers of cardiovascular control. Calculation of HRV from the peripheral pulse wave using PPG, called pulse rate variability (PRV), is investigated. The current work has confirmed that the PPG signal could provide basic information about heart rate (HR) and its variability, and highly suggests a good alternative to understanding dynamics pertaining to the autonomic nervous system (ANS) without the use of an electrocardiogram (ECG) device. Hence, PPG measurement has the potential to be readily accepted in ambulatory cardiac monitoring due to its simplicity and comfort. Noncontact PPG (NPPG) is introduced to overcome the current limitations of contact PPG. As a contactless device, NPPG is especially attractive for physiological monitoring in ambulatory units, NICUs, or trauma centres, where attaching electrodes is either inconvenient or unfeasible. In this research, a prototype for noncontact reflection PPG (NRPPG) with a vertical cavity surface emitting laser (VCSEL) as a light source and a high-speed PiN photodiode as a photodetector is developed. The results from physiological experiments suggest that NRPPG is reliable to extract clinically useful information about cardiac condition and function. In summary, recent evidence demonstrates that PPG as a simple noninvasive measurement offers a fruitful avenue for noninvasive cardiovascular monitoring. Key words: Photoplethysmography (PPG), Cardiovascular assessment, Pulse wave contour analysis, Arterial stiffness, Heart rate (HR), Heart rate variability (HRV), Pulse rate variability (PRV), Autonomic nervous system (ANS), Electrocardiogram (ECG).
34
Gunzenhauser, Jan. "Application of real-time HRV biofeedback in the scenario of meditation practice : Feasibility, usability and medical fidelity." Thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-45420.
Full textAbstract:
Chronic stress is a prevalent and universally present hazard in modern society. It lowers the quality of life for individuals and significantly con- tributes to unsustainable health care costs. Therefore it is important to have natural and noninvasive ways of controlling stress. One such way is meditation, a technique which has been practiced for over five thousand years to improve stress regulation. Also, proceedings in sensing technologies lead to the discovery of biofeedback as another cost-effective technique for stress assessment and reduction. In continuation of research on real-time reflective human-computer-interfaces, this thesis combines these techniques by exploring the application of electrocardiography sensing technology in a heart rate variability (HRV) biofeedback system for the scenario of medita- tion practice. A proof-of-concept prototype was designed and implemented which quantifies stress and gives feedback on meditation effectiveness. For evaluation, a user study has been performed. Results were analysed in a systematic way to evaluate the feasibility and acceptance of the solution as well as the fidelity of HRV data that was measured during user tests. The prototype was found to be feasible in the context of technology acceptance while the fidelity of data, acquired by an algorithm for time and frequency domain analysis of HRV, was confirmed. A final conclusion is that the reflective aspect of the implemented real-time biofeedback system helps to improve regulatory capacity and thus lowers stress in individuals.
35
Moreno, Sánchez Jordi. "Esport, salut i HRV: monitorització psicofisiològica de l’estrès i la recuperació amb dispositius mòbils." Doctoral thesis, Universitat Autònoma de Barcelona, 2015. http://hdl.handle.net/10803/298302.
Full textAbstract:
El risc de desenvolupar una Síndrome de Sobreentrenament és un dels factors a tenir més en compte en la preparació esportiva. En aquest sentit, una correcta recuperació és determinant per a garantir una adaptació funcional de l'esportista als entrenaments i a les competicions. L'avaluació contínua de la recuperació des d'una perspectiva psicofisiològica pot aportar informació sobre l'estat real de l'esportista, però es requereixen eines i metodologies que permetin monitoritzar la recuperació d'una forma ràpida, a temps real i no invasiva en l'entorn natural de l'esportista. En aquest context, els dos objectius principals d'aquesta tesi doctoral són: 1) Analitzar la utilitat de les tècniques de seismocardiografia (SCG) i fotopletismografia (PPG) per a l'anàlisi de la HRV; i 2) Proposar la monitorització psicofisiològica del procés d’estrès i recuperació com a eina d'Avaluació Ecològica Momentània (EMA) en situacions esportives, a partir de l’anàlisi combinada de la HRV i d’indicadors cognitius i conductuals. En aquesta Tesi Doctoral s'han realitzat sis estudis, tres corresponents a la part d'innovació en la metodologia d'anàlisi de la HRV, i tres més en la part d'aplicació de l'anàlisi de la HRV en context esportiu. Dins de la primera part de la tesi, es proposen les tècniques de SCG i PPG com a vàlides per a l'estimació dels intervals R-R i la posterior anàlisi de la HRV. En el cas de l'ús de la SCG, els resultats mostren que són necessàries unes condicions de registre estrictes en posició supina, de repòs total i que cal personalitzar la col·locació del dispositiu sobre l'estèrnum de la persona per millorar la qualitat del senyal. El senyal de SCG dels dispositius iPhone es mostra com a tècnica eficaç per la monitorització a distància de l'esportista prescindint de cap accessori addicional. En el cas de la PPG facial, els resultats mostren que la posició supina és més optima que la d'assegut. Tot i que les condicions de registre són massa estrictes com per utilitzar-se en un context esportiu natural pot resultat eficaç en contextos hospitalaris per al seguiment de pacients en un entorn controlat. Dins de la segona part de la tesi, es proposa l'anàlisi HRV per a la determinació de perfils específics en funció de la modalitat esportiva. Aquesta metodologia podria ajudar a determinar la predisposició de l’esportista cap a una determinada modalitat esportiva o a valorar l'adaptació de l'esportista en comparació a la resta de companys que segueixen el mateix pla d'entrenament. L'anàlisi combinada de la HRV amb l'estat d'ànim de forma puntual és útil per detectar estats de Vigor o Fatiga, però insuficient per a detectar perfils de Tensió, Depressió o Hostilitat. També es proposa l'ús de l'EMA com a metodologia útil per a la detecció de perfils psicofisiològics de recuperació, suggerint la necessitat d'analitzar i d'interpretar els paràmetres de HRV de forma individual enlloc d'utilitzar barems poblacionals. En el cas de la respiració, els resultats indiquen que el protocol utilitzat en la recollida de dades (respiració espontània o pautada) influeix directament en els valors dels paràmetres de domini freqüencial, provocant biaixos en la interpretació de l'estat d'estrès-recuperació avaluat a partir de qüestionaris. En aquest sentit, els resultats mostren que la respiració espontània aporta informació més rellevant sobre l'estat d'estrès de l'esportista. A partir dels resultats obtinguts en aquesta tesi doctoral, es proposa l’ús dels smartphones per analitzar la HRV, l’estat d’ànim i aspectes conductuals referents a la recuperació o als estils de vida, segons un model d’EMA i d’una forma no-invasiva, gràcies a la tecnologia integrada en els sensors propis. El sistema resultant, aplicat al camp esportiu, permet una monitorització psicofisiològica del procés d’estrès-recuperació.The risk of developing overtraining syndrome is a factor to be taken into account in preparing sport. In this sense, proper recovery is crucial to ensure a functional adaptation of the athlete in training and competitions. Continuous assessment of recovery from a psychophysiological perspective can provide information about the actual state of the athlete, but require tools and methodologies that allow to monitor the recovery with fast, in real-time and non-invasive in the natural environment of the athlete. In this context, the two main objectives of this thesis are: 1) Analyse the usefulness of seismocardiography (SCG) and photoplethysmography (PPG) for the analysis of HRV; and 2) Propose the psychophysiological monitoring of the stress and recovery process as a tool of Ecological Momentary Assessment (EMA) in sport situations, from the combined analysis of HRV and cognitive and behavioural indicators. In this Doctoral Thesis has been performed six studies, three related with innovation methodology for analysis of HRV, and three more related with the application of the analysis of HRV in the sport context. In the first part of the thesis, we propose techniques SCG and PPG as a valid to estimate of RR intervals and subsequent analysis of HRV. In the case of the use of the SCG, the results show that is necessary a stringent conditions of record in supine position, total rest and the importance to customize the placement of the device on the sternum of the person to improve the quality signal. SCG signal of iPhone is an effective technique for remote monitoring of the athlete without additional accessory. In the case of facial PPG, the results show that the supine position is more optimal than the sitting position. Although the registration conditions are too strict as for use in a sport context can be effective in natural contexts of hospital for monitoring patients in a controlled environment. In the second part of the thesis proposes HRV analysis for the determination of specific profiles depending on the sport. This methodology could help to determine the predisposition of the athlete to a sport modality or to evaluate the adaptation of the athlete compared to other colleagues who follow the same training plan. The combined analysis of HRV with the mood in a timely evaluation is useful for detecting states of Vigour or Fatigue, but not enough to detect profiles of Tension, Depression or Hostility. Also proposed the use of EMA as a useful methodology for detecting psychophysiological profiles of recovery, suggesting the need to analyse and interpret the HRV parameters individually instead of using scales population. In the case of breathing, the results indicate that the protocol used in the data collection (spontaneous or paced breathing) directly influences the values of the parameters of frequency domain, causing bias in the interpretation of the state of stress-recovery assessed with questionnaires. In this sense, the results show that spontaneous breathing provides relevant information about the state of stress of the athlete. From the results obtained in this thesis, we propose the use of smartphones to analyse HRV, mood and behavioural aspects relating to the recovery or lifestyles, according to a model of EMA and to a non-invasive technology thanks to the integrated sensors themselves. The resulting system, applied to the sports field, allows monitoring of psychophysiological stress-recovery process.
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Smith, Brianna. "Assessing the relationship between resting autonomic nervous system functioning, social anxiety, and emotional autobiographical memory retrieval." Thesis, Boston College, 2018. http://hdl.handle.net/2345/bc-ir:108097.
Full textAbstract:
Thesis advisor: Elizabeth KensingerIndividuals with social anxiety disorder (SAD) tend to have emotional memory biases in the encoding and retrieval of social memories. Research has shown reduced heart rate variability (HRV) in clinical populations suffering from anxiety, including social anxiety. Heightened sympathetic activation—as measured by the electrodermal activity (EDA)—has also been associated with anxiety disorders. The aim of the present study was to examine the relation between HRV, social anxiety, and re-experiencing of emotional autobiographical memories. 44 healthy young adults were recruited from the Boston College campus through SONA. Participants were given an online survey that instructed them to retrieve 40 specific events from the past in response to 40 socially relevant cues. For each event, participants were instructed to provide a brief narrative, make several ratings for the event (on a scale from 1-7), and indicate the specific emotions they experienced both at the time of retrieval and of the event. Approximately one month after the completion of the memory survey, participants engaged in a 2-hour memory retrieval session while undergoing psychophysiological monitoring (heart rate, skin conductance, and respiration). Following the retrieval task, participants completed self-report questionnaires of social anxiety symptom severity and trait emotion regulation strategy (i.e., tendency to reappraise or suppress emotions). The present study found that positive memories had higher re-experiencing ratings as compared to negative memories. Contrary to the original study hypothesis, however, there was no significant interaction between average re-experiencing (or arousal) ratings of positive or negative social autobiographical memories and SAD likelihood. A nonlinear, cubic relationship was found between one of three metrics of HRV and social anxiety symptom severity. A significant effect was found between skin conductance and SAD likelihood, which was likely driven by an almost significance difference in skin conductance between the SAD unlikely and the SAD very probable groups; these findings provide further insight into the relationship between autonomic nervous system (ANS) functioning and social anxiety. Further, the present results suggest the intriguing possibility that there may be a nonlinear relationship between HRV and severity of social anxiety. Future research with a larger sample size is needed to corroborate these findings
Thesis (BS) — Boston College, 2018
Submitted to: Boston College. College of Arts and Sciences
Discipline: Departmental Honors
Discipline: Psychology
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Dizon, Lucas, and Martin Johansson. "Atrial Fibrillation Detection Algorithm Evaluation and Implementation in Java." Thesis, KTH, Skolan för teknik och hälsa (STH), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-158878.
Full textAbstract:
Atrial fibrillation is a common heart arrhythmia which is characterized by a missing or irregular contraction of the atria. The disease is a risk factor for other more serious diseases and the total medical costs in society are extensive. Therefore it would be beneficial to improve and optimize the prevention and detection of the disease. Pulse palpation and heart auscultation can facilitate the detection of atrial fibrillation clinically, but the diagnosis is generally confirmed by an ECG examination. Today there are several algorithms that detect atrial fibrillation by analysing an ECG. A common method is to study the heart rate variability (HRV) and by different types of statistical calculations find episodes of atrial fibrillation which deviates from normal sinus rhythm. Two algorithms for detection of atrial fibrillation have been evaluated in Matlab. One is based on the coefficient of variation and the other uses a logistic regression model. Training and testing of the algorithms were done with data from the Physionet MIT database. Several steps of signal processing were used to remove different types of noise and artefacts before the data could be used. When testing the algorithms, the CV algorithm performed with a sensitivity of 91,38%, a specificity of 93,93% and accuracy of 92,92%, and the results of the logistic regression algorithm was a sensitivity of 97,23%, specificity of 93,79% and accuracy of 95,39%. The logistic regression algorithm performed better and was chosen for implementation in Java, where it achieved a sensitivity of 97,31%, specificity of 93,47% and accuracy of 95,25%.Förmaksflimmer är en vanlig hjärtrytmrubbning som kännetecknas av en avsaknad eller oregelbunden kontraktion av förmaken. Sjukdomen är en riskfaktor för andra allvarligare sjukdomar och de totala kostnaderna för samhället är betydande. Det skulle därför vara fördelaktigt att effektivisera och förbättra prevention samt diagnostisering av förmaksflimmer. Kliniskt diagnostiseras förmaksflimmer med hjälp av till exempel pulspalpation och auskultation av hjärtat, men diagnosen brukar fastställas med en EKG-undersökning. Det finns idag flertalet algoritmer för att detektera arytmin genom att analysera ett EKG. En av de vanligaste metoderna är att undersöka variabiliteten av hjärtrytmen (HRV) och utföra olika sorters statistiska beräkningar som kan upptäcka episoder av förmaksflimmer som avviker från en normal sinusrytm. I detta projekt har två metoder för att detektera förmaksflimmer utvärderats i Matlab, en baseras på beräkningar av variationskoefficienten och den andra använder sig av logistisk regression. EKG som kommer från databasen Physionet MIT används för att träna och testa modeller av algoritmerna. Innan EKG-signalen kan användas måste den behandlas för att ta bort olika typer av brus och artefakter. Vid test av algoritmen med variationskoefficienten blev resultatet en sensitivitet på 91,38%, en specificitet på 93,93% och en noggrannhet på 92,92%. För logistisk regression blev sensitiviteten 97,23%, specificiteten 93,79% och noggrannheten 95,39%. Algoritmen med logistisk regression presterade bättre och valdes därför för att implementeras i Java, där uppnåddes en sensitivitet på 91,31%, en specificitet på 93,47% och en noggrannhet på 95,25%.
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Bonomi, Mattia. "Facial-based Analysis Tools: Engagement Measurements and Forensics Applications." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/271342.
Full textAbstract:
The last advancements in technology leads to an easy acquisition and spreading of multi-dimensional multimedia content, e.g. videos, which in many cases depict human faces. From such videos, valuable information describing the intrinsic characteristic of the recorded user can be retrieved: the features extracted from the facial patch are relevant descriptors that allow for the measurement of subject's emotional status or the identification of synthetic characters.
One of the emerging challenges is the development of contactless approaches based on face analysis aiming at measuring the emotional status of the subject without placing sensors that limit or bias his experience. This raises even more interest in the context of Quality of Experience (QoE) measurement, or the measurement of user emotional status when subjected to a multimedia content, since it allows for retrieving the overall acceptability of the content as perceived by the end user. Measuring the impact of a given content to the user can have many implications from both the content producer and the end-user perspectives.
For this reason, we pursue the QoE assessment of a user watching multimedia stimuli, i.e. 3D-movies, through the analysis of his facial features acquired by means of contactless approaches. More specifically, the user's Heart Rate (HR) was retrieved by using computer vision techniques applied to the facial recording of the subject and then analysed in order to compute the level of engagement. We show that the proposed framework is effective for long video sequences, being robust to facial movements and illumination changes. We validate it on a dataset of 64 sequences where users observe 3D movies selected to induce variations in users' emotional status.
From one hand understanding the interaction between the user's perception of the content and his cognitive-emotional aspects leads to many opportunities to content producers, which may influence people's emotional statuses according to needs that can be driven by political, social, or business interests. On the other hand, the end-user must be aware of the authenticity of the content being watched: advancements in computer renderings allowed for the spreading of fake subjects in videos.
Because of this, as a second challenge we target the identification of CG characters in videos by applying two different approaches. We firstly exploit the idea that fake characters do not present any pulse rate signal, while humans' pulse rate is expressed by a sinusoidal signal. The application of computer vision techniques on a facial video allows for the contactless estimation of the subject's HR, thus leading to the identification of signals that lack of a strong sinusoidality, which represent virtual humans. The proposed pipeline allows for a fully automated discrimination, validated on a dataset consisting of 104 videos. Secondly, we make use of facial spatio-temporal texture dynamics that reveal the artefacts introduced by computer renderings techniques when creating a manipulation, e.g. face swapping, on videos depicting human faces. To do so, we consider multiple temporal video segments on which we estimated multi-dimensional (spatial and temporal) texture features. A binary decision of the joint analysis of such features is applied to strengthen the classification accuracy. This is achieved through the use of Local Derivative Patterns on Three Orthogonal Planes (LDP-TOP). Experimental analyses on state-of-the-art datasets of manipulated videos show the discriminative power of such descriptors in separating real and manipulated sequences and identifying the creation method used.
The main finding of this thesis is the relevance of facial features in describing intrinsic characteristics of humans. These can be used to retrieve significant information like the physiological response to multimedia stimuli or the authenticity of the human being itself. The application of the proposed approaches also on benchmark dataset returned good results, thus demonstrating real advancements in this research field. In addition to that, these methods can be extended to different practical application, from the autonomous driving safety checks to the identification of spoofing attacks, from the medical check-ups when doing sports to the users' engagement measurement when watching advertising. Because of this, we encourage further investigations in such direction, in order to improve the robustness of the methods, thus allowing for the application to increasingly challenging scenarios.
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Bonomi, Mattia. "Facial-based Analysis Tools: Engagement Measurements and Forensics Applications." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/271342.
Full textAbstract:
The last advancements in technology leads to an easy acquisition and spreading of multi-dimensional multimedia content, e.g. videos, which in many cases depict human faces. From such videos, valuable information describing the intrinsic characteristic of the recorded user can be retrieved: the features extracted from the facial patch are relevant descriptors that allow for the measurement of subject's emotional status or the identification of synthetic characters.
One of the emerging challenges is the development of contactless approaches based on face analysis aiming at measuring the emotional status of the subject without placing sensors that limit or bias his experience. This raises even more interest in the context of Quality of Experience (QoE) measurement, or the measurement of user emotional status when subjected to a multimedia content, since it allows for retrieving the overall acceptability of the content as perceived by the end user. Measuring the impact of a given content to the user can have many implications from both the content producer and the end-user perspectives.
For this reason, we pursue the QoE assessment of a user watching multimedia stimuli, i.e. 3D-movies, through the analysis of his facial features acquired by means of contactless approaches. More specifically, the user's Heart Rate (HR) was retrieved by using computer vision techniques applied to the facial recording of the subject and then analysed in order to compute the level of engagement. We show that the proposed framework is effective for long video sequences, being robust to facial movements and illumination changes. We validate it on a dataset of 64 sequences where users observe 3D movies selected to induce variations in users' emotional status.
From one hand understanding the interaction between the user's perception of the content and his cognitive-emotional aspects leads to many opportunities to content producers, which may influence people's emotional statuses according to needs that can be driven by political, social, or business interests. On the other hand, the end-user must be aware of the authenticity of the content being watched: advancements in computer renderings allowed for the spreading of fake subjects in videos.
Because of this, as a second challenge we target the identification of CG characters in videos by applying two different approaches. We firstly exploit the idea that fake characters do not present any pulse rate signal, while humans' pulse rate is expressed by a sinusoidal signal. The application of computer vision techniques on a facial video allows for the contactless estimation of the subject's HR, thus leading to the identification of signals that lack of a strong sinusoidality, which represent virtual humans. The proposed pipeline allows for a fully automated discrimination, validated on a dataset consisting of 104 videos. Secondly, we make use of facial spatio-temporal texture dynamics that reveal the artefacts introduced by computer renderings techniques when creating a manipulation, e.g. face swapping, on videos depicting human faces. To do so, we consider multiple temporal video segments on which we estimated multi-dimensional (spatial and temporal) texture features. A binary decision of the joint analysis of such features is applied to strengthen the classification accuracy. This is achieved through the use of Local Derivative Patterns on Three Orthogonal Planes (LDP-TOP). Experimental analyses on state-of-the-art datasets of manipulated videos show the discriminative power of such descriptors in separating real and manipulated sequences and identifying the creation method used.
The main finding of this thesis is the relevance of facial features in describing intrinsic characteristics of humans. These can be used to retrieve significant information like the physiological response to multimedia stimuli or the authenticity of the human being itself. The application of the proposed approaches also on benchmark dataset returned good results, thus demonstrating real advancements in this research field. In addition to that, these methods can be extended to different practical application, from the autonomous driving safety checks to the identification of spoofing attacks, from the medical check-ups when doing sports to the users' engagement measurement when watching advertising. Because of this, we encourage further investigations in such direction, in order to improve the robustness of the methods, thus allowing for the application to increasingly challenging scenarios.
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Tiinanen, S. (Suvi). "Methods for assessment of autonomic nervous system activity from cardiorespiratory signals." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526223131.
Full textAbstract:
Abstract A cardiorespiratory system is highly regulated via the autonomic nervous system (ANS), whose function can be quantified noninvasively by analyzing electrocardiogram (ECG), blood pressure (BP) and respiration signals. Several conditions and illnesses are linked with imbalance of the ANS. This thesis aimed to develop methods for describing the ANS regulation of a cardiovascular system from short-term cardiorespiratory measurements. More specifically, the role of breathing rate and its effects on traditional frequency domain based cardiovascular indexes describing ANS control is addressed. The main contributions are as follows: 1) an adaptive filtering based method to remove respiratory influences from cardiovascular signals and indexes was developed. The adaptive filter reduced the bias caused by low respiration rate, enabling the usage of spontaneous respiration measurement protocol over controlled respiration. 2) Methods to quantify respiratory sinus arrhythmia (RSA) index from cardiovascular signals were developed as well: two methods utilizes adaptive filtering and either the measured respiration signal or the ECG-derived respiration signal and one method uses independent component analysis. Developed RSA index methods allow varying respiration rates making them physiologically more accurate than traditional high frequency power with fixed respiration rate, often used as RSA index. 3) Tools for studying the power and the frequency of low frequency (LF) oscillations of cardiovascular signals were developed, including a time-frequency representation for analyzing varying data. An experimental study was conducted with patients of continuum of cardiovascular risks. According to results, aging decreased the frequency of LF oscillation, whereas coronary artery disease decreased it further. 4) Two new ECG-derived respiration (EDR) methods utilizing decomposition techniques were developed. The proposed methods yielded statistically significant improvements over previously developed EDR methods. EDR method enables to get respiratory information from ECG, which in its turn reduces needed modalities in ANS quantification. This thesis provides methods to quantify indexes describing the ANS function more accurately by acknowledging the respiration effects. The results of this thesis may be utilized in various application areas, ranging from clinical to physiology research up to commercial health, wellness and sport productsTiivistelmä Autonominen hermosto säätelee tarkasti sydän- ja verenkiertoelimistöä sekä hengitystä. Autonomisen hermoston toimintaa voidaan analysoida laskennallisin menetelmin noninvasiivisesti mitatuista elektrokardiogrammi- (EKG, sydänsähkökäyrä), verenpaine- ja hengityssignaaleista. Useita tekijöitä ja sairauksia voidaan yhdistää autonomisen hermoston epätasapainoon. Väitöskirjassa kehitettiin menetelmiä sydän- ja verisuonijärjestelmän autonomisen säätelyn kuvaamiseksi lyhytaikaisista kardiorespiratorisista tallenteista. Erityistä huomiota on kiinnitetty hengityksen vaikutukseen perinteisiin taajuustasosta laskettaviin muuttujiin, jotka kuvaavat autonomisen hermoston toimintaa. Väitöskirjan päätuloksia ja -tuotoksia ovat: 1) uusi adaptiiviseen suodatukseen pohjautuva laskennallinen menetelmä hengitysvaikutuksien poistamiseksi sydän- ja verisuonisignaaleista. Adaptiivinen suodatin vähensi matalan hengitystaajuuden aiheuttamaa vääristymää hermoston toimintaa kuvaavista parametreistä. Uusi menetelmä mahdollistaa kontrolloimattoman eli vapaan hengitystaajuus-protokollan käytön autonomisen hermoston toiminnan mittauksissa. 2) Uusia menetelmiä respiratorisen sinus arrytmian (RSA) määrittämiseksi sydän- ja verisuonisignaaleista. Kehitetyissä menetelmistä kahdessa käytetään adaptiivista suodatusta hyödyntäen joko mitattua hengityssignaalia tai EKG:stä johdettua hengityssignaalia. Kolmas menetelmä pohjautuu itsenäisten komponenttien analyysiin. Kehitetyt menetelmät RSA:n laskemiseksi sallivat hengitystaajuuden vaihtelun mittauksien aikana, mikä tekee ne fysiologisesti tarkemmaksi kuin perinteisesti käytetty korkeataajuinen (HF) komponentti, joka lasketaan taajuustasossa tietyltä kaistalta riippumatta hengitystaajuudesta. 3) Kehitettiin ja sovellettiin menetelmiä EKG:n ja verenpaineen matalataajuisten (LF) heilahtelujen tutkimista varten. Yhdessä tutkimuksessa sovellettiin aika-taajuustason esitystapaa vaihtelevan datan analysoimiksi. Kokeellinen tutkimus tehtiin aineistolla, joka oli jatkumo sydän- ja verisuonitautien riskejä omaavista potilaista jo sairastuneisiin potilaisiin. Ikääntyminen pienensi matalataajuisen heilahtelun taajuutta ja sepelvaltimosairaus pienensi sitä edelleen. 4) Kaksi uutta hajotelmatekniikoita hyödyntävää menetelmää, joilla lasketaan EKG:stä hengitysvirtausignaali-estimaatti (EDR). Kehitettyjen EDR-menetelmien suorituskyky osoittautui tilastollisesti paremmaksi kuin aikaisemmat menetelmät. Koska hengityssignaali ja -taajuus voidaan johtaa suoraan EKG:stä, tarvittavien mittaussensoreiden määrää vähenee. Lisäksi EDR:ää voidaan hyödyttää autonomisen hermoston toimintaa kuvaavien parametrien estimoinnissa. Väitöskirja tarjoaa menetelmiä autonomisen hermoston toiminnan mittaamiseksi huomioiden erityisesti hengityksen vaikutus estimoitaviin parametreihin. Väitöskirjan tuloksia voidaan soveltaa useissa kardiorespiratorisia signaaleja hyödyntävissä sovelluksissa aina kliinisestä työstä fysiologian tutkimukseen ja kaupallisiin hyvinvointi-, terveys- ja urheilusovelluksiin
Huomautus/Notice Painetussa virheellinen ISBN: 978-952-62-2312-4, oikea 978-952-62-2310-0. Printed version has incorrect ISBN: 978-952-62-2312-4, it should be 978-952-62-2310-0
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Cassirame, Johan. "Intérêts et limites de l'utilisation de l'analyse de la variabilité de la fréquence cardiaque pour la pratique sportive." Thesis, Besançon, 2015. http://www.theses.fr/2015BESA3001/document.
Full textAbstract:
L'analyse de la Variabilité de la Fréquence Cardiaque est une méthode de mesure non invasive du Système Nerveux Autonome. Cette méthode d'analyse initialement utilisée dans le domaine clinique s'est progressivement installée dans le domaine de l'activité physique pour diverses applications telles que la détection précoce de la fatigue, le calibrage de l'intensité de l'entraînement, détecter les seuils ventilatoires... Les méthodes d'analyse peuvent être utilisées hors contexte de laboratoire, mais nécessitent néanmoins une attention particulière du point de vue méthodologique pour être cohérentes vis-à-vis des concepts mathématiques ou physiologiques qui les régissent. Chaque étape de cette méthode nécessite une rigueur spécifique pour ne pas conduire à une mauvaise interprétation. Ce document détaille le processus depuis la phase de mesure de l'intervalle RR en étudiant notamment la précision des appareils utilisables sur le terrain ou la correction du périodogramme obtenu en proposant différentes méthodes. Ce travail décrit également les indices de l'analyse de la VFC et les différentes limites techniques et conceptuelles. Les différents facteurs et biais influençant l'état du tonus du Système Nerveux Autonome seront décrits pour faciliter la création d'un protocole et l'analyse des indices de la VFC obtenusHeart Rate Variability Analysis is a non-invasive method for the evaluation of the Autonomic Nervous System activity. This analytical method initially used for clinical diagnosis progressively installed in the field of physical activity for various applications such as early detection of overreaching, calibration of training intensity, ventilatory threshold determination... These methods can be used outside the laboratory environment, but still require particular attention from a methodological aspect in order to be consistent with mathematical or physiological concepts underlying. Each step of this method requires a specific discipline not to lead to misinterpretation. This document details the process from the RR interval measurement phase including accuracy assessment of the devices used in the field or signal treatment with artifacts correction proposing several methods. This work details index from HRV analysis with their technical and conceptual limitations. External factors mat influence the Autonomic Nervous System are described to facilitate the protocol creation and results interpretation
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Benešová, Lenka. "Vyhodnocení variability rychlosti pulzové vlny." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400981.
Full textAbstract:
This diploma thesis deals with the variability of pulse wave velocity. It studies the variability of cardiovascular signals. It presents the research of measurement of pulse wave velocity and its analysis in physiology and pathological physiology. Applies spectral analysis in Matlab to a data set. It evaluates and reviews the results of this analysis
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Röstin, Martin. "Development of a Flexible Software Framework for Biosignal PI : An Open-Source Biosignal Acquisition and Processing System." Thesis, KTH, Skolan för teknik och hälsa (STH), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183525.
Full textAbstract:
As the world population ages, the healthcare system is facing new challenges in treating more patients at a lower cost than today. One trend in addressing this problem is to increase the opportunities of in-home care. To achieve this there is a need for safe and cost-effective monitoring systems. Biosignal PI is an ongoing open-source project created to develop a flexible and affordable platform for development of stand-alone devices able to measure and process physiological signals. This master thesis project, performed at the department of Medical Sensors, Signals and System at the School of Technology and Health, aimed at further develop the Biosignal PI software by constructing a new flexible software framework architecture that could be used for measurement and processing of different types of biosignals. The project also aimed at implementing features for Heart Rate Variability(HRV) Analysis in the Biosignal PI software as well as developing a graphical user interface(GUI) for the Raspberry PI hardware module PiFace Control and Display. The project developed a new flexible abstract software framework for the Biosignal PI. The new framework was constructed to abstract all hardware specifics into smaller interchangeable modules, with the idea of the modules being independent in handling their specific task making it possible to make changes in the Biosignal PI software without having to rewrite all of the core. The new developed Biosignal PI software framework was implemented into the existing hardware setup consisting of an Raspberry PI, a small and affordable single-board computer, connected to ADAS1000, a low power analog front end capable of recording an Electrocardiography(ECG). To control the Biosignal PI software two different GUIs were implemented. One GUI extending the original software GUI with the added feature of making it able to perform HRV-Analysis on the Raspberry PI. This GUI requires a mouse and computer screen to function. To be able to control the Biosignal PI without mouse the project also created a GUI for the PiFace Control and Display. The PiFace GUI enables the user to collect and store ECG signals without the need of an big computer screen, increasing the mobility of the Biosignal PI device. To help with the development process and also to make the project more compliant with the Medical Device Directive a couple of development tools were implemented such as a CMake build system, integrating the project with the Googletest testing framework for automated testing and the implementation of the document generator software Doxygen to be able to create an Software Documentation. The Biosignal PI software developed in this thesis is available through Github at https://github.com/biosignalpi/Version-A1-Rapsberry-PIAllt eftersom världens befolkning åldras, ställs sjukvården inför nya utmaningar i att behandla fler patienter till en lägre kostnad än idag. En trend för att lösa detta problem är att utöka möjligheterna till vård i hemmet.För att kunna göra detta finns det ett ökande behov av säkra och kostnadseffektiva patientövervakningssystem. Biosignal PI är ett pågående projekt med öppen källkod som skapats för att utveckla en flexibel och prisvärd plattform för utveckling av fristående enheter som kan mäta och bearbeta olika fysiologiska signaler. Detta examensarbete genomfördes vid institutionen för medicinska sensorer, signaler och system vid Skolan för Teknik och Hälsa. Projektet syftade till att vidareutveckla den befintliga mjukvaran för Biosignal PI genom att skapa ett nytt flexibelt mjukvaruramverk som kan användas för mätning och bearbetning av olika typer av biosignaler.Projektet syftade också till att utvidga mjukvaran och lägga till funktioner för att kunna genomföra hjärtfrekvensvariabilitets(HRV) analys i Biosignal PIs mjukvara, samt att utveckla ett grafiskt användargränssnitt(GUI) för hårdvarumodulen PiFace Control and Display. Projektet har utvecklat ett nytt flexibelt mjukvaruramverk för Biosignal PI. Det nya ramverket konstruerades för att abstrahera alla hårdvaruspecifika delar in i mindre utbytbara moduler, med tanken att modulerna ska vara oberoende i hur de hanterar sin specifika uppgift. På så sätt ska det vara möjligt att göra ändringar i Biosignal PIs programvara utan att behöva skriva om hela mjukvaran.Det nyutvecklade Biosignal PI ramverket implementerades i det befintliga hårdvaru systemet, som består av en Raspberry PI, liten och prisvärd enkortsdator, ansluten till ADAS1000, en analog hårdvarumodul med möjlighet att registrera ett elektrokardiografi(EKG/ECG). För att kontrollera Biosignal PI programmet har två olika grafiska användargränssnitt skapats.Det ena gränssnitt är en utvidgning av original programvaran med tillagd funktionalitet för att kunna göra HRV-Analys på Raspberry PI, detta gränssnitt kräver dock mus och dataskärm för att kunna användas.För att kunna styra Biosignal PI utan mus och skärm skapades det även ett gränssnitt för PiFace Control and Display. PiFace gränssnittet gör det möjligt för användaren att samla in och lagra EKG-signaler utan att behöva en stor datorskärm, på så sätt kan man öka Biosignal PI systemets mobilitet. För att underlätta utvecklingsprocessen, samt göra projektet mer förenligt med det medicintekniska regelverket, har ett par utvecklingsverktyg integrerats till Biosignal PI projektet såsom CMake för kontroll av kompileringsprocessen, test ramverket Googletest för automatiserad testning samt integrering med dokumentations generatorn Doxygen för att kunna skapa en dokumentation av mjukvaran.
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Doyen, Matthieu. "Méthodes probabilistes pour le monitoring cardio-respiratoire des nouveau-nés prématurés." Thesis, Rennes 1, 2018. http://www.theses.fr/2018REN1S049/document.
Full textAbstract:
La surveillance des nouveau-nés prématurés placés en unité de soins intensifs a conduit à la notion de monitoring et à l'acquisition de nombreux signaux physiologiques. Si ces informations sont bien utilisées pour le diagnostic et la prévention des situations d'urgence, force est de constater qu'à ce jour, elles le sont beaucoup moins dans un objectif prédictif. La difficulté d'extraction d'informations fiables en temps réel, sans aucun contrôle visuel, à partir de signaux non stationnaires, en est vraisemblablement la cause. Ce mémoire vise donc à proposer des méthodes robustes, adaptées au contexte des unités de soins intensifs néonatals et du temps réel. Pour cela, un ensemble de méthodes génériques appliquées à la variabilité cardiaque, mais capable d'être adaptées à d'autres constantes physiologiques telles que la respiration, ont été développées et testées en contexte clinique. Quatre grandes parties illustrent notre propos : - La proposition d'une méthode originale de détection temps réel probabiliste multicaractéristique permettant de répondre à une problématique d'extraction robuste d'événements d'intérêt à partir de signaux physiologiques bruités. Générique, cette solution est appliquée à la détection robuste du QRS d'un signal ECG. Elle est basée sur le calcul temps réel de plusieurs probabilités a posteriori, concernant les propriétés du signal, qui sont ensuite fusionnées au sein d'un nœud de décision reposant sur l'utilisation pondérée de la divergence de Kullback-Leibler. Comparée à deux méthodes classiques de la littérature sur deux bases de données bruitées, elle obtient un taux d'erreur de détection inférieur (20.91% vs 29.02% (ondelettes) et 33.08% (Pan-Tompkins) sur la base de test). - La proposition d'une méthode impliquant plusieurs modèles semi-markoviens cachés, visant la segmentation de périodes au sein desquelles le détecteur temps réel probabiliste multicaractéristique fournit les détections d'évènements les plus fiables. En comparaison à deux méthodes de la littérature, la solution proposée obtient de meilleures performances, le critère d‘erreur obtenu est significativement plus faible (entre -21.37% et -74.98% selon la base et l'approche évaluée). - La sélection d'un détecteur optimal pour le monitoring d'événements d'apnée-bradycardie, en termes de fiabilité et précocité, à partir de données ECG obtenues chez le nouveau-né. Les performances du détecteur retenu seront comparées aux alarmes générées par un dispositif industriel de suivi continu classiquement utilisé en service de néonatalogie (moniteur Philips IntelliVue). La méthode basée sur le changement abrupt de la moyenne des RR obtient les meilleurs résultats au regard du délai (3.99 s vs 11.53 s pour le moniteur IntelliVue) et de la fiabilité (critère d'erreur de 43.60% vs 80.40%). - La conception et le développement d'une plateforme logicielle SYNaPSE (SYstem for Noninvasive Physiological Signal Explorations) permettant l'acquisition de divers signaux physiologiques en très grande quantité, et de façon non invasive, au sein des unités de soins. La conception modulaire de cette plateforme, ainsi que ses propriétés temps réel, permettent l'intégration simple et rapide de méthodes de traitement du signal complexes. Son intérêt translationnel est montré dans le dépouillement d'une base de données cherchant à étudier l'impact de la bilirubine sur la variabilité cardiaqueThe surveillance of premature newborns placed in intensive care units led to the notion of monitoring and the acquisition of many physiological signals. While this information is well used for the diagnosis and prevention of emergency situations, it must be acknowledged that, to date, it is less the case for predictive purposes. This is mainly due to the difficulty of extracting reliable information in real time, without any visual control, from non-stationary signals. This thesis aims to propose robust methods, adapted to the context of neonatal intensive care units and real time. For this purpose, a set of generic methods applied to cardiac variability, but capable of being adapted to other physiological constants such as respiration, have been developed and tested in clinical context. Four main parts illustrate these points : - The proposal of an original multicharacteristic probabilistic real time detection method for robust detection of interest events of noisy physiological signals. Generic, this solution is applied to the robust QRS complex detection of the ECG signals. It is based on the real time calculation of several posterior probabilities of the signal properties before merging them into a decision node using the weighted Kullback-Leibler divergence. Compared to two classic methods from the literature on two noisy databases, it has a lower detection error rate (20.91% vs. 29.02% (wavelets) and 33.08% (Pan-Tompkins) on the test database). - The proposal of using hidden semi-markovian models for the segmentation of temporal periods with most reliable event detections. Compared to two methods from the literature, the proposed solution achieves better performance, the error criterion obtained is significantly lower (between -21.37% and -74.98% depending on the basis and approach evaluated). - The selection of an optimal detector for the monitoring of apnea-bradycardia events, in terms of reliability and precocity, based on ECG data obtained from newborns. The performance of the selected detector will be compared to the alarms generated by an industrial continuous monitoring device traditionally used in neonatology service (Philips IntelliVue monitor). The method based on the abrupt change of the RR average achieves the best results in terms of time (3.99 s vs. 11.53 s for the IntelliVue monitor) and reliability (error criterion of 43.60% vs. 80.40%). - The design and development of SYNaPSE (SYstem for Noninvasive Physiological Signal Explorations) software platform for the acquisition of various physiological signals in large quantities, and in a non-invasive way, within the care units. The modular design of this platform, as well as its real time properties, allows simple and fast integration of complex signal processing methods. Its translational interest is shown in the analysis of a database in order to study the impact of bilirubin on cardiac variability
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Silva, Luiz Eduardo Virgilio da. "Análise do sinal de variabilidade da frequência cardíaca através de estatística não extensiva: taxa de q-entropia multiescala." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/59/59135/tde-22032013-114045/.
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O corpo humano é um sistema complexo composto por vários subsistemas interdependentes, que interagem entre si em várias escalas. Sabe-se que essa complexidade fisiológica tende a diminuir com a presença de doenças e com o avanço da idade, reduzindo a capacidade de adaptação dos indivíduos. No sistema cardiovascular, uma das maneira de se avaliar sua dinâmica regulatória é através da análise da variabilidade da frequência cardíaca (VFC). Os métodos clássicos de análise da VFC são baseados em modelos lineares, como é o caso da análise espectral. Contudo, como os mecanismos fisiológicos de regulação cardíaca apresentam características não lineares, as análises utilizando tais modelos podem ser limitadas. Nos últimos tempos, várias propostas de métodos não lineares têm surgido. Porém, não se sabe de uma medida consistente com o conceito de complexidade fisiológica, onde tanto os regimes periódicos como aleatórios são caracterizados como perda de complexidade. Baseado no conceito de complexidade fisiológica, esta tese propõe novos métodos de análise não lineares para séries de VFC. Os métodos consistem da generalização de medidas de entropia já existentes, utilizando a mecânica estatística não aditiva de Tsallis e a técnica de geração de dados substitutos. Foi definido um método, chamado de qSDiff, que calcula a diferença entre a entropia de um sinal e a entropia média de suas séries substitutas. O método de entropia utilizado consiste de uma generalização da entropia amostral (SampEn), utilizando o paradigma não aditivo. Das séries qSDiff foram extraídos três atributos, que foram avaliados como possíveis índices de complexidade fisiológica. A entropia multiescala (MSE) também foi generalizada seguindo o paradigma não aditivo, e os mesmos atributos foram calculados em várias escalas. Os métodos foram aplicados em séries reais de VFC de humanos e de ratos, bem como em um conjunto de sinais simulados, formado por ruídos e mapas, este último em regimes caótico e periódico. O atributo qSDiffmax demonstrou ser consistente para baixas escalas ao passo que os atributos qmax e qzero para escalas maiores, separando e classificando os grupos quanto à complexidade fisiológica. Observou-se ainda uma possível relação entre estes q-atributos com a presença de caos, que precisa ser melhor estudada. Os resultados ainda apontam a possibilidade de que, na insuficiência cardíaca, ocorre maior degradação nos mecanismos de baixa escala, de curto período, ao passo que na fibrilação atrial o prejuízo se estenderia para escalas maiores. As medidas baseadas em entropia propostas são capazes de extrair informações importantes das séries de VFC, sendo mais consistentes com o conceito de complexidade fisiológica do que a SampEn (clássica). Reforçou-se a hipótese de que a complexidade se revela em múltiplas escalas de um sinal. Acreditamos que os métodos propostos podem contribuir bastante na análise da VFC e também de outros sinais biomédicos.Human body is a complex system composed of several interdependent subsystems, interacting at various scales. It is known that physiological complexity tends to decrease with disease and aging, reducing the adaptative capabilities of the individual. In the cardiovascular system, one way to evaluate its regulatory dynamics is through the analysis of heart rate variability (HRV). Classical methods of HRV analysis are based on linear models, such as spectral analysis. However, as the physiological mechanisms regulating heart rate exhibit nonlinear characteristics, analyzes using such models may be limited. In the last years, several proposals nonlinear methods have emerged. Nevertheless, no one is known to be consistent with the physiological complexity theory, where both periodic and random regimes are characterized as complexity loss. Based on physiological complexity theory, this thesis proposes new methods for nonlinear HRV series analysis. The methods are generalization of existing entropy measures, through Tsallis nonadditive statistical mechanics and surrogate data. We defined a method, called qSDiff, which calculates the difference between the entropy of a signal and its surrogate data average entropy. The entropy method used is a generalization of sample entropy (SampEn), through nonadditive paradigm. From qSDiff we extracted three attributes, which were evaluated as potential physiological complexity indexes. Multiscale entropy (MSE) was also generalized following nonadditive paradigm, and the same attributes were calculated at various scales. The methods were applied to real human and rats HRV series, as well as to a set of simulated signals, consisting of noises and maps, the latter in chaotic and periodic regimes. qSDiffmax attribute proved to be consistent for low scales while qmax and qzero attributes to larger scales, separating and ranking groups in terms of physiological complexity. There was also found a possible relationship between these q-attributes with the presence of chaos, which must be further investigated. The results also suggested the possibility that, in congestive heart failure, degradation occurs rather at small scales or short time mechanisms, while in atrial fibrillation, damage would extend to larger scales. The proposed entropy based measures are able to extract important information of HRV series, being more consistent with physiological complexity theory than SampEn (classical). Results strengthened the hypothesis that complexity is revealed at multiple scales. We believe that the proposed methods can contribute to HRV as well as to other biomedical signals analysis.
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Schaffner, Markus. "Behavioural evidence for social preferences." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/48898/1/Markus_Schaffner_Thesis.pdf.
Full textAbstract:
A central topic in economics is the existence of social preferences. Behavioural economics in general has approached the issue from several angles. Controlled experimental settings, surveys, and field experiments are able to show that in a number of economic environments, people usually care about immaterial things such as fairness or equity of allocations. Findings from experimental economics specifically have lead to large increase in theories addressing social preferences. Most (pro)social phenomena are well understood in the experimental settings but very difficult to observe 'in the wild'. One criticism in this regard is that many findings are bound by the artificial environment of the computer lab or survey method used. A further criticism is that the traditional methods also fail to directly attribute the observed behaviour to the mental constructs that are expected to stand behind them. This thesis will first examine the usefulness of sports data to test social preference models in a field environment, thus overcoming limitations of the lab with regards to applicability to other - non-artificial - environments. The second major contribution of this research establishes a new neuroscientific tool - the measurement of the heart rate variability - to observe participants' emotional reactions in a traditional experimental setup.
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Claesson, Maria. "Women's hearts : ischaemic heart disease and stress management in women." Doctoral thesis, Umeå : Department of Public Health and Clinical Medicine, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-725.
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Ede, David E. Jr. "Trait Mindfulness and Cardiovascular Reactivity and Recovery During a Laboratory Mental Stress Protocol in Young Adults." Kent State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=kent1524140223472705.
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Duque, Juliano Jinzenji. "Avaliação da q-transformada de Fourier como ferramenta não linear de estudos de sinais biomédicos." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/59/59135/tde-29112012-121139/.
Full textAbstract:
A análise de sinais biomédicos é uma área de pesquisa importante pois diversos processos fisiológicos que ocorrem no corpo humano podem ter suas atividades registradas como sinais. Neste trabalho, investigou-se a q-transformada de Fourier (q-FT), uma generalização não linear da transformada de Fourier baseada no formalismo não extensivo de Tsallis, que é caracterizado pela presença do parâmetro q. Foram realizados estudos analíticos e experimentos computacionais com sinais reais e simulados. A partir da dfinição da q-FT, um método de análise espectral generalizado para aplicação em sinais biomédicos foi desenvolvido. Este método foi avaliado através de experimentos com séries de intervalos RR cardíacos, usadas em estudos de variabilidade da frequência cardíaca. Os resultados ajudam a esclarecer algumas propriedades desta q-transformada, porém não indicam que o método desenvolvido seja efetivo para a análise espectral de séries RR. Entretanto, estudos posteriores de novos métodos de análise espectral baseados no formalismo de Tsallis podem ser desenvolvidos para a investigação de sinais biomédicos.Biomedical signals analysis is an important research eld because many physiological processes occurring in human body can have their activities recorded as signals.This study investigated the q-Fourier transform (q-FT), a nonlinear generalization of Fourier transform based on the Tsallis nonextensive formalism, which is characterized by q parameter. Analytical studies and computational experiments with simulated and real signals were conducted. From the denition of q-FT, a generalized spectral analysis method for application in biomedical signals has been developed. This method was assessed through experiments with cardiac RR interval time series, which are used in studies of heart rate variability. The results help to clarify some properties of the q-Fourier transform, but do not indicate that the developed method is efective for the spectral analysis of RR series. However, further studies on new spectral analysis methods based on Tsallis formalism can be developed for biomedical signals investigation.
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Friberg, Annika. "Interaktionskvalitet - hur mäts det?" Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20810.
Full textAbstract:
Den tekniska utvecklingen har lett till att massiva mängder av information sänds, i högahastigheter. Detta flöde måste vi lära oss att hantera. För att maximera nyttan av de nyateknikerna och undkomma de problem som detta enorma informationsflöde bär med sig, börinteraktionskvalitet studeras. Vi måste anpassa gränssnitt efter användaren eftersom denneinte har möjlighet att anpassa sig till, och sortera i för stora informationsmängder. Vi måsteutveckla system som gör människan mer effektiv vid användande av gränssnitt.För att anpassa gränssnitten efter användarens behov och begränsningar krävs kunskaperom den mänskliga kognitionen. När kognitiv belastning studeras är det viktigt att en såflexibel, lättillgänglig och icke-påträngande teknik som möjligt används för att få objektivamätresultat, samtidigt som pålitligheten är av största vikt. För att kunna designa gränssnittmed hög interaktionskvalitet krävs en teknik att utvärdera dessa. Målet med uppsatsen är attfastställa en mätmetod väl lämpad för mätning av interaktionskvalitet.För mätning av interaktionskvalitet rekommenderas en kombinering av subjektiva ochfysiologiska mätmetoder, detta innefattar en kombination av Functional near-infraredspecroscopy; en fysiologisk mätmetod som mäter hjärnaktiviteten med hjälp av ljuskällor ochdetektorer som fästs på frontalloben, Electrodermal activity; en fysiologisk mätmetod sommäter hjärnaktiviteten med hjälp av elektroder som fästs över skalpen och NASA task loadindex; en subjektiv, multidimensionell mätmetod som bygger på kortsortering och mäteruppfattad kognitiv belastning i en sammanhängande skala. Mätning med hjälp av dessametoder kan resultera i en ökad interaktionskvalitet i interaktiva, fysiska och digitalagränssnitt. En uppskattning av interaktionskvalitet kan bidra till att fel vid interaktionminimeras, vilket innebär en förbättring av användares upplevelse vid interaktion.Technical developments have led to the broadcasting of massive amounts of information, athigh velocities. We must learn to handle this flow. To maximize the benefits of newtechnologies and avoid the problems that this immense information flow brings, interactionquality should be studied. We must adjust interfaces to the user because the user does nothave the ability to adapt and sort overly large amounts of information. We must developsystems that make the human more efficient when using interfaces.To adjust the interfaces to the user needs and limitations, knowledge about humancognitive processes is required. When cognitive workload is studied it is important that aflexible, easily accessed and non assertive technique is used to get unbiased results. At thesame time reliability is of great importance. To design interfaces with high interaction quality,a technique to evaluate these is required. The aim of this paper is to establish a method that iswell suited for measurement of interaction quality.When measuring interaction quality, a combination of subjective and physiologicalmethods is recommended. This comprises a combination of Functional near-infraredspectroscopy; a physiological measurement which measures brain activity using light sourcesand detectors placed on the frontal lobe, Electrodermal activity; a physiological measurementwhich measures brain activity using electrodes placed over the scalp and NASA task loadindex; a subjective, multidimensional measurement based on card sorting and measures theindividual perceived cognitive workload on a continuum scale. Measuring with these methodscan result in an increase in interaction quality in interactive, physical and digital interfaces.An estimation of interaction quality can contribute to eliminate interaction errors, thusimproving the user’s interaction experience.