Dissertations / Theses on the topic 'Health IT artifact'

Lung cancer remains the leading cause of cancer deaths in the United States despite public health campaigns aimed at reducing its rate of mortality. Kentucky is the state with the highest lung cancer incidence and mortality. This study aims to assess the impact of misclassification of cause of death from Lung Cancer in Kentucky for the period 1979 to 2002. We will examine the potential competing classification of death for two other smoking-related diseases, Chronic Obstructive Pulmonary Disease (COPD) and Emphysema. Age-adjusted mortality rates for these diseases for white males were obtained from the National Center for Health Statistics. There was little evidence that any misclassification between COPD or Emphysema mortality rates was in agreement with the rising lung cancer rates in Kentucky. The long-term increase in lung cancer mortality in Kentucky is likely because of a combination of risk effects between smoking and other risk-factors for this disease.

The IT artifact is at the core of the information systems (IS) discipline and yet most IS research does not directly theorize the IT artifact or its nomological network (Benbasat and Zmud 2003; Orlikowski and Iacono 2001). This research seeks to answer a repeated call for more direct engagement with the IT artifact and its nomological net with affordance theory adopted as the basis for this theoretical work. An exploratory case study was conducted to answer the research question, how do the material properties of health information systems enable and constrain the work practices of clinicians? The study was conducted at a large urban acute care hospital in the Midwestern United States with registered nurses working on inpatient care units as the clinicians of interest. Through interviews with nurses and other clinical stakeholders and the observation of nurse’s work practices on three patient care units in the hospital, theoretical insights were developed on the nature of affordances for information systems research. IS affordances are defined in this study as relationships between abilities of an individual and features of an information systems within the context of the environment in which they function. The concepts of an affordance range and an affordance threshold are proposed as theoretical constructs in the nomological network of affordances that help to explain the use of information systems as a function of the difficulty of acting on IS affordances. The relationship between affordances and constraints is theorized and linked to the affordance range and threshold with the assertion that constraints are closely associated with the difficulties experienced by users in acting on IS affordances. The challenge of studying IS affordances in all their complexity is discussed with the suggestion that researchers take the user’s perspective of affordances to alleviate the need for repeated decomposition. Finally, the role of information systems in facilitating social interaction is emphasized through the concept of affordances for sociality. The contribution of this research to the IS field is a more nuanced understanding of the nature of the IT artifact and its relationship to the users of that technology.

Despite having the numerous evolved heart rate measuring devices and progress in their development over the years, there always remain the challenges of modern signal processing implementation by a comparatively small size wearable device. This thesis paper presents a wearable reflectance photoplethysmography (PPG) sensor system for measuring the heart rate of a user both in steady and moving states. The size and, power consumption of the device are considered while developing, to ensure an easy deployment of the unit at the measuring site and the ability to power the entire unit with a battery .The selection of both the electronic circuits and signal processing techniques is based on their sensitivity to PPG signals, robustness against noise inducing artifacts and miniaturization of the entire measuring unit. The entire signal chain operates in the discrete-time, which allows the entire signal processing to be implemented in firmware on an embedded microprocessor. The PPG sensor system is implemented on a single PCB that consumes around 7.5mW of power. Benchmarking tests with standard heart rate measuring devices reveal that the developed measurement unit (combination of the PPG sensor system, and inertial measurement unit (IMU) developed in-house at Acreo Swedish ICT, and a battery) is comparable to the devices in detecting heart rate even in motion artifacts environment. This thesis work is carried out in Acreo Swedish ICT, Gothenburg, Sweden in collaboration with MidSweden University, Sundsvall, Department of Electronics Design. This report can be used as ground work for future development of wearable heart rate measuring units at Acreo Swedish ICT.

The aim of the thesis is to study the role of instruction in the interconnection of instruction-learning-development. The thesis consists of six empirical papers and a summing-up and perspectivizing introductory paper. Five of the empirical studies concern so called heart conferences, clinical diagnostic meetings, which at the time of my study, 1995-1996, were arranged as telemediated conferences between a sub-team of surgeons and radiologists in a university clinic, and a sub-team of cardiologists and radiologists in a regional hospital. The outcome of the coronary diagnostic work in the heart conferences was patient diagnoses and decided-upon treatment (surgery, balloon dilatation, or conservative treatment). The sixth empirical study, conducted in the autumn 2000, investigates the design and redesign of a central artifact used in the heart conference, ?the angio film,? produced in the angio lab. A recurrent theme in the empirical papers is whether artifacts might be instructive and, if so, in what ways. The introductory paper is a hybrid between an ordinary summing-up paper of the findings in the empirical studies, and a perspectivizing presentation of activity-theoretical approaches to instruction, learning and development, elaborating on three basic aspects (learning as a collaborative phenomenon, the instructiveness of artifacts, and the relation between learning and development on an individual level, but primarily on an activity level). In conclusion, my study outlines an approach to learning based on new perspectives on instruction.
Studier av läkares co-coaching av varandra som ett led i deras samarbete rörande kranskärlsdiagnostiskt arbete. Artefaktanvändning, lärande och versamhetsutveckling.

Over the past decade, there has been an increasing interest in the real-time monitoring of ambulatory vital signs such as heart rate (HR) and arterial blood oxygen saturation (SpO2) using wearable medical sensors during field operations. These measurements can convey valuable information regarding the state of health and allow first responders and front-line medics to better monitor and prioritize medical intervention of military combatants, firefighters, miners and mountaineers in case of medical emergencies. However, the primary challenge encountered when using these sensors in a non-clinical environment has been the presence of persistent motion artifacts (MA) embedded in the acquired physiological signal. These artifacts are caused by the random displacement of the sensor from the skin and lead to erroneous output readings. Several signal processing techniques, such as time and frequency domain segmentation, signal reconstruction techniques and adaptive noise cancellation (ANC), have been previously developed in an offline environment to address MA in photoplethysmography (PPG) with varying degrees of success. However, the performance of these algorithms in a spasmodic noise environment usually associated with basic day to day ambulatory activities has still not been fully investigated. Therefore, the focus of this research has been to develop novel MA algorithms to combat the effects of these artifacts. The specific aim of this thesis was to design two novel motion artifact (MA) algorithms using a combination of higher order statistical tools namely Kurtosis (K) for classifying 10 s PPG data segments, as either ‘clean’ or ‘corrupt’ and then extracting the aforementioned vital parameters. To overcome the effects of MA, the first algorithm (termed ‘MNA’) processes these ‘corrupt’ PPG data segments by identifying abnormal amplitudes changes. The second algorithm (termed ‘MNAC’), filters these ‘corrupt’ data segments using a 16th order normalized least mean square (NLMS) ANC filter and then extracts HR and SpO2.

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.

Pulse oximetry is used to measure heart rate (HR) and arterial oxygen saturation (SpO2) from photoplethysmographic (PPG) waveforms. PPG waveforms are highly sensitive to motion artifact (MA), limiting the implementation of pulse oximetry in mobile physiological monitoring using wearable devices. Previous studies have shown that multichannel pulse oximetry can successfully acquire diverse signal information during simple, repetitive motion, thus leading to differences in motion tolerance across channels. In this study, we introduce a multichannel forehead-mounted pulse oximeter and investigate the performance of this novel sensor under a variety of intense motion artifacts. We have developed a multichannel template-matching algorithm that chooses the channel with the least amount of motion artifact to calculate HR and SpO2 every 2 seconds. We show that for a wide variety of random motion, channels respond differently to motion, and the multichannel estimate outperforms single channel estimates in terms of motion tolerance, signal quality, and HR and SpO2 error. Based on 31 data sets of PPG waveforms corrupted by random motion, the mean relative HR error was decreased by an average of 5.6 bpm when the multichannel-switching algorithm was compared to the worst performing channel. The percentage of HR measurements with absolute errors ≤ 5 bpm during motion increased by an average of 27.8 % when the multichannel-switching algorithm was compared to the worst performing channel. Similarly, the mean relative SpO2 error was decreased by an average of 4.3 % during motion when the multichannel-switching algorithm was compared to each individual channel. The percentage of SpO2 measurements with absolute error ≤ 3 % during motion increased by an average of 40.7 % when the multichannel-switching algorithm was compared to the worst performing channel. Implementation of this multichannel algorithm in a wearable device will decrease dropouts in HR and SpO2 measurements during motion. Additionally, the differences in motion frequency introduced across channels observed in this study shows precedence for future multichannel-based algorithms that make pulse oximetry measurements more robust during a greater variety of intense motion.

PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
Esta dissertação de Mestrado teve por objetivo a concepção, desenvolvimento e validação de um dispositivo opto-eletrônico, que opera na faixa do infravermelho, para detecção e medição da velocidade de esferas em meios turvos. A motivação para desenvolvimento deste tema resultou da necessidade de controlar a circulação de esferas para instrumentar um sistema alternativo de limpeza de trocadores de calor de hidrogeradores, que faz uso de artefatos abrasivos de geometria esférica. O método utilizado fundamenta-se no processamento do sinal eletrônico gerado por um circuito que produz pulsos proporcionais ao tempo de passagem da esfera no interior do contador, a cada interrupção do feixe luminoso. O tratamento do sinal, gerado por pares de sensores opto-eletrônicos perpendiculares entre si e montados transversalmente ao fluxo de água de resfriamento que transporta as esferas, é realizado por um controlador lógico programável, que atribui inteligência ao sistema. Dentre os resultados obtidos, constatou-se que o dispositivo consegue detectar esferas circulantes quando transportadas por fluxos de água com diferentes graus de turbidez (ensaios em laboratório) ou quando em operação no ambiente da usina hidrelétrica, cuja opacidade da água de resfriamento é dada pela incrustação removida durante o processo de limpeza. Como conclusão, pode-se afirmar que o dispositivo opto-eletrônico proposto atende às necessidades do projeto de construção de um sistema alternativo de limpeza por esferas abrasivas, conseguindo descartar falsos positivos na contagem das esferas, a exemplo de bolhas de ar ou partículas de incrustação cujas dimensões críticas diferem daquelas das esferas abrasivas.
This dissertation aimed at the design, development and validation of an optoelectronic device, operating in the infrared range, for counting and measuring the velocity of spheres in turbid media. The motivation to develop this theme resulted from the need to control the spheres circulation to implement an alternative system for cleaning heat exchangers used to cool hydrogenerators, which make use of spherical abrasive artefacts. The methodology used is based on the processing of the electronic signal generated by a circuit that produces pulses proportional to the time of passage of the sphere inside the meter, at each interruption of the light beam. The processing of the signal, which is generated by pairs of mutually perpendicular optoelectronic sensors and mounted transversely to the flow of cooling water carrying the spheres, is performed by a programmable logic controller, which provides intelligence to the system. Among the obtained results, it was verified that the device can detect circulating spheres both when transported by water flows with different degrees of turbidity (laboratory tests) and when in operation in the environment of the hydroelectric plant, whose opacity of the cooling water is given by the fouling removed during the cleaning process. As a conclusion, it can be stated that the proposed optoelectronic device meets the needs of the construction of the alternative system of cleaning by abrasive spheres and can eliminate false positives in the counting of the spheres, such as air bubbles or incrustation particles whose critical dimensions differ from those of the abrasive spheres.

Syfte: Att ta reda på hur lång livslängd en bildplatta har avseende slitage och bildkvalité.Material och metod: Tre fabriksnya bildplattor användes för att undersöka hur en enskild faktor i arbetsgången för bildgenerering påverkar bildkvalitén. Den första plattan exponerades och skannades 300 gånger. Platta nummer två användes för att undersöka effekten av totalt 300 av- och påtagningar i en frigolithållare, och platta tre användes för motsvarande test av en plasthållare. Exponering skedde utan patient och mot en neutral bakgrund. För samtliga plattor togs i initialskedet en referensbild, och resulterande bilder från testerna granskades i Planmeca Romexis 3.8 och bedömdes enligt en skala 0-3. Plattorna i sig granskades även okulärt, och test av uniformitet gjordes av referensbild och bild 300 i serie 1 med hjälp av ImageJ. Resultat: Samtliga bilder från samtliga plattor bedömdes vara likvärdiga med referensbild. Vid okulär granskning var reporna klart mer uttalade hos den platta som skannats 300 gånger, men reporna återfanns endast på den sida som ej är avsedd att exponeras. Test av uniformitet fann ingen skillnad mellan referensbild och bild nr 300 i serie 1. Slutsats: Studien visar att varken röntgenexponering, skanning eller av- och påtagning i hållare av två olika slag har någon inverkan på bildkvalité efter 300 upprepningar då momenten gjordes var för sig. Vi konkluderar att plattan sannolikt är som mest sårbar då den placeras intraoralt, och föreslår att alla moment gjorda i följd delvis kan svara för den reduktion av bildkvalité som observerats i andra studier.
Aim: To determine the longevity of photostimulable storage phosphor plates (PSPs) with respect to wear and image quality. Method: Three brand new PSPs were used to assess how a solitary factor in the picture generation process affects the picture quality. The first plate was exposed and scanned 300 times. Plate number two was used to assess the effect of mounting and demounting the plate 300 times onto a holder made of styrofoam, and the third plate was used for a corresponding test with a plastic holder. A flat surface was exposed and no patients were involved. A reference picture was taken initially for each plate, and the resulting pictures from the tests were viewed using Planmeca Romexis 3.8 and were evaluated on a scale from 0-3. The individual plates also underwent ocular inspection, and a uniformity test was performed on the first and last picture taken with plate 1, using ImageJ. Results: Each picture from each plate was deemed equivalent to the reference picture. The ocular inspection revealed a more distinct band of scratches on the plate that was scanned the most, although the scratches were only found on the side not meant to receive exposure. No difference in uniformity was found between the first and last picture taken using plate 1. Conclusion: X-ray exposure, scanning and mounting and demounting of PSPs onto holders of two different kinds do not affect the picture quality after 300 repetitions when done separately. We conclude that the plate is likely most susceptible to wear when placed intraorally, and suggest that all the steps made in succession can partly account for the reduction in picture quality observed in other studies.

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Heart rate monitoring using Photoplethysmography (PPG) signals acquired from the individuals pulse has become popular due to emergence of numerous low cost wearable devices. However, monitoring during physical activities has obstacles because of the influence of motion artifacts in PPG signals. The objective of this work is to introduce a new algorithm capable of removing motion artifacts and estimating heart rate from pulse PPG signals. Normalized Least Mean Square (NLMS) and Recursive Least Squares (RLS) algorithms are proposed for an adaptive filtering structure that uses acceleration signals as reference to remove motion artifacts. The algorithm uses the Periodogram of the filtered signals to extract their heart rates, which will be used together with a PPG Signal Quality Index to feed the input of a Kalman Filter. Specific heuristics and the Quality Index collaborate so that the Kalman filter provides a heart rate estimate with high accuracy and robustness to measurement uncertainties. The algorithm was validated from the heart rate obtained from Electrocardiography signals and the proposed method with the RLS algorithm presented the best results with an absolute mean error of 1.54 beats per minute (bpm) and standard deviation of 0.62 bpm, recorded for 12 individuals performing a running activity on a treadmill with varying speeds. The results make the performance of the algorithm comparable and even better than several recently developed methods in this field. In addition, the algorithm presented a low computational cost and suitable to the time interval in which the heart rate estimate is performed. Thus, it is expected that this algorithm will improve the obtaining of heart rate in currently available wearable devices.
O monitoramento da frequ?ncia card?aca utilizando sinais de Fotopletismografia ou PPG (do ingl?s, Photopletismography) adquiridos do pulso de indiv?duos tem se popularizado devido ao surgimento de in?meros dispositivos wearable de baixo custo. No entanto, o monitoramento durante atividades f?sicas tem dificuldades em raz?o da influ?ncia de artefatos de movimento nos sinais de PPG. O objetivo deste trabalho ? introduzir um novo algoritmo capaz de remover artefatos de movimento e estimar a frequ?ncia card?aca de sinais de PPG de pulso. Os algoritmos do M?nimo Quadrado M?dio Normalizado ou NLMS (do ingl?s, Normalized Least Mean Square) e de M?nimos Quadrados Recursivos ou RLS (do ingl?s, Recursive Least Squares) s?o propostos para uma estrutura de filtragem adaptativa que utiliza sinais de acelera??o como refer?ncia para remover os artefatos de movimento. O algoritmo utiliza o Periodograma dos sinais filtrados para extrair suas frequ?ncias card?acas, que ser?o utilizadas juntamente com um ?ndice de Qualidade do Sinal de PPG para alimentar a entrada de um Filtro de Kalman. Heur?sticas espec?ficas e o ?ndice de Qualidade colaboram para que filtro de Kalman forne?a uma estimativa da frequ?ncia card?aca com alta acur?cia e robustez a incertezas de medi??o. O algoritmo foi validado a partir da frequ?ncia card?aca obtida de sinais de Eletrocardiografia e o m?todo proposto com o algoritmo RLS apresentou os melhores resultados com um erro m?dio absoluto de 1,54 batimentos por minuto (bpm) e desvio padr?o de 0,62 bpm, registrados para 12 indiv?duos realizando uma atividade de corrida em uma esteira com velocidades variadas. Os resultados tornam o desempenho do algoritmo compar?vel e at? mesmo melhor que v?rios m?todos desenvolvidos recentemente neste campo. Al?m disso, o algoritmo apresentou um custo computacional baixo e adequado ao intervalo de tempo em que a estimativa da frequ?ncia card?aca ? realizada. Dessa forma, espera-se que este algoritmo melhore a obten??o da frequ?ncia card?aca em dispositivos wearable atualmente dispon?veis.

In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes.

碩士
國立清華大學
電機工程學系
99
A pulse oximeter is a noninvasive oxyhemoglobin saturation monitoring instrument with optical components. When developing miniaturization and wireless communication technologies, small sized portable health care system are demanded. Therefore, continuous health care monitoring and precaution device for emergency are required for the patient. To develop the device on these demands, the sensing interface circuit is requested to minimize for protable reason and the photoplethysmographic to be reduce noise. The major source of noise is body motion, for this reason, motion artifact reduction is the key technique to develop. In this paper, a portable sensing interface circuit and a motion artifact reduction method was proposed. The device had a shape of the finger band, which measured the photoplethysmographic on the finger. For the purpose of a portable device, components of the transimpedance ampligier, LED driver, analog multiplexer, and filters, were integrated into a printed circuit board. Moreover, the transconductance-C filter of low-pass filter, band-pass filter, and notch filter, were integrated into a chip using TSMC 0.18μm technology. Finally, this research presents a motion artifact reduction method with correction of optical calculation and active noise cancellation method with a reference signal to reduce signal distortion by body motion.

碩士
國立中央大學
電機工程學系
102
This research was aimed at reducing the error caused by motion artifacts in a heart rate detection system to be applied in wearable devices. The heart rate signal was obtained by using the photoplethysmography (PPG) sensor. The PPG sensor we designed consists of a PWM modulator, an infrared LED, a light dependent resistor (LDR), a demodulator, a high-pass filter, a low-pass filter, and an amplification circuit. Furthermore, a 3-axis accelerometer sensor was used to sense the body motion at the PPG sensor site. The output of the accelerometer sensor may have a considerable correlation with the motion artifact in the heart rate signal. Both the PPG heart rate signal and the accelerometer output signal were sampled and digitized through a data acquisition system of a personal computer. The reduction of motion artifact and the heart rate detection were conducted by the MATLAB program in the computer. Taking the accelerometer output signal as the reference signal, an active noise cancellation (ANC) algorithm recovered the corrupted heart rate signal from motion artifact. The performance of the active noise cancellation is evaluated using a commercial heart-rate belt as the golden standard. The heart rate detection error of our system is 3.52% with a small motion, 8.81% with a big motion, and 4.32% with a 1-Hz motion. The result of our experiments proves that the active noise cancellation method is suitable for removing motion artifact from heart rate signal even if there is overlapping between the spectra of the motion artifact and the heart rate signal.

Les artéfacts métalliques entraînent un épaississement artéfactuel de la paroi des tuteurs en tomodensitométrie (TDM) avec réduction apparente de leur lumière. Cette étude transversale prospective, devis mesures répétées et observateurs avec méthode en aveugle, chez 24 patients consécutifs/71 tuteurs coronariens a pour objectif de comparer l’épaisseur de paroi des tuteurs en TDM après reconstruction par un algorithme avec renforcement des bords et un algorithme standard. Une angiographie coronarienne par TDM 256 coupes a été réalisée, avec reconstruction par algorithmes avec renforcement des bords et standard. L’épaisseur de paroi des tuteurs était mesurée par méthodes orthogonale (diamètres) et circonférentielle (circonférences). La qualité d’image des tuteurs était évaluée par échelle ordinale, et les données analysées par modèles linéaire mixte et régression logistique des cotes proportionnelles. L’épaisseur de paroi des tuteurs était inférieure avec l’algorithme avec renforcement des bords comparé à l’algorithme standard, avec les méthodes orthogonale (0,97±0,02 vs 1,09±0,03 mm, respectivement; p<0,001) et circonférentielle (1,13±0,02 vs 1,21±0,02 mm, respectivement; p<0,001). Le premier causait moins de surestimation par rapport à l’épaisseur nominale comparé au second, avec méthodes orthogonale (0,89±0,19 vs 1,00±0,26 mm, respectivement; p<0,001) et circonférentielle (1,06±0,26 vs 1,13±0,31 mm, respectivement; p=0,005) et diminuait de 6 % la surestimation. Les scores de qualité étaient meilleurs avec l’algorithme avec renforcement des bords (OR 3,71; IC 95% 2,33–5,92; p<0,001). En conclusion, la reconstruction des images avec l’algorithme avec renforcement des bords génère des parois de tuteurs plus minces, moins de surestimation, et de meilleurs scores de qualité d’image que l’algorithme standard.
Metallic artifacts can result in an artificial thickening of the coronary stent wall which can significantly impair computed tomography (CT) imaging in patients with coronary stents. The purpose of this study is to assess the in vivo visualization of coronary stent wall and lumen with an edge-enhancing CT reconstruction kernel, as compared to a standard kernel. This is a prospective cross-sectional study of 24 consecutive patients with 71 coronary stents, using a repeated measure design and blinded observers, approved by the Local Institutional Review Board. 256-slice CT angiography was used, as well as standard and edge-enhancing reconstruction kernels. Stent wall thickness was measured with orthogonal and circumference methods, averaging wall thickness from stent diameter and circumference measurements, respectively. Stent image quality was assessed on an ordinal scale. Statistical analysis used linear and proportional odds models. Stent wall thickness was inferior using the edge-enhancing kernel compared to the standard kernel, either with the orthogonal (0.97±0.02 versus 1.09±0.03 mm, respectively; p<0.001) or circumference method (1.13±0.02 versus 1.21±0.02 mm, respectively; p<0.001). The edge-enhancing kernel generated less overestimation from nominal thickness compared to the standard kernel, both with orthogonal (0.89±0.19 versus 1.00±0.26 mm, respectively; p<0.001) and circumference (1.06±0.26 versus 1.13±0.31 mm, respectively; p=0.005) methods. The average decrease in stent wall thickness overestimation with an edge-enhancing kernel was 6%. Image quality scores were higher with the edge-enhancing kernel (odds ratio 3.71, 95% CI 2.33–5.92; p<0.001). In conclusion, the edge-enhancing CT reconstruction kernel generated thinner stent walls, less overestimation from nominal thickness, and better image quality scores than the standard kernel.

Tese de doutoramento em Ciências e Tecnologias da Informação, apresentada ao Departamento de Engenharia Informática da Faculdade de Ciências e Tecnologia da Universidade de Coimbra
As doenças cardiovasculares (CVDs) são atualmente a principal causa de morte no mundo e são responsáveis por mais de 7 milhões de mortes todos os anos. A mortalidade decorrente das CVDs tem vindo aumentar, principalmente devido ao crescimento da população nos países de baixo e médio rendimento, que alojam cerca de 85% da população mundial. Nos países de elevado rendimento, o acesso a melhores tecnologias de diagnostico e melhores terapêuticas, bem como estilos de vida mais saudáveis, inverteram esta tendência e a mortalidade resultante das CVDs está a decrescer. Este facto, aliado ao aumento da esperança média de vida das populações, leva a que as pessoas sejam afectadas ou morram devido a CVDs em idades mais avançadas, contribuindo para o aumento dos gastos com a saúde em todo o mundo. Uma condição que contribui largamente para este problema é a síncope, que têm um impacto económico equivalente a doenças como a asma, HIV e doença pulmonar obstrutiva crónica. Mais conhecida como “desmaio”, a síncope está associada a uma frequência elevada de quedas e de hospitalizações, e é responsável por uma menor a qualidade de vida, especialmente em populações mais idosas. Para enfrentar os encargos socioeconómicos derivados das CVDs, o paradigma da saúde tem vindo a mudar de reativo e centralizado nos hospitais para preventivo e centrado em cada individuo, com um foco especial no diagnostico precoce e em melhores estratégias de prevenção e gestão das CVDs. Assim, o desenvolvimento de novas metodologias para monitorização da função cardiovascular, capazes de serem aplicadas em sistemas de baixo custo, não invasivos e portáteis, são essenciais para a prevenção e controlo desta crescente epidemia que são as CVDs. Apesar dos recentes avanços tecnológicos, as técnicas padrão atuais para a avaliação da função cardiovascular, como a ressonância magnética cardíaca e ecocardiografia, ainda apresentam várias limitações no que diz respeito à sua aplicação em ambientes de saúde personalizada. Assim, a utilização de modalidades amplamente disponíveis e de baixo custo, como o eletrocardiograma e o fotopletismograma, para a avaliação não-invasiva, contínua e de longo prazo da função cardiovascular pode ser a chave para melhores estratégias de prevenção e gestão de doenças cardiovasculares. Mais concretamente, a extração de parâmetros cardiovasculares a partir destas modalidades pode ser crucial na predição de síncopes e prevenção de quedas. A principal contribuição da presente tese consiste no desenvolvimento de novos algoritmos para a avaliação continua, não invasiva e robusta da função cardiovascular, com base na análise do eletrocardiograma e do fotopletismograma. Visto que o fotopletismograma é facilmente afectado por ruído e artefactos de movimento, o que representa um obstáculo para a extração de parâmetros cardiovasculares, é fundamental detectar quais as secções do fotopletismograma passiveis de serem posteriormente analisadas. Assim, propomos um novo método para detecção de artefactos de movimento baseado na extração e análise de características do domínio temporal e de período. Consequentemente, propomos um novo algoritmo para a estimação do tempo de ejecção do ventrículo esquerdo, o qual está associado com a função cardíaca, bem como outros parâmetros relacionados com alterações de pressão sanguínea e de tónus vascular. Finalmente, propomos um novo algoritmo para a predição de síncopes (mais especificamente, síncope neuromediada) baseada na avaliação dos parâmetros previamente extraídos. Os métodos propostos foram validados em três bases de dados, coligidas no Departamento de Engenharia Informática da Universidade de Coimbra, no Centro Hospitalar da Universidade de Coimbra e no departamento de Eletrofisiologia do Centro Universitário do Coração, Hospital Universitário de Eppendorf, Hamburgo, Alemanha.
Cardiovascular diseases (CVDs) are currently the leading cause of death in the world and are responsible for over 17 million deaths per year. The mortality of CVDs is increasing, mainly driven by the increase of the population in low and middle income countries, which house about 85% of the world’s population. In high-income countries, the access to better diagnostic and therapeutic technologies, as well as healthier life stiles, reverses this tendency and CVD mortality is decreasing. In combination with the increase in the populations’ life expectancy, people are affected or die as a result of CVD at older ages, contributing to the rise in the health care expenditures all over the world. A condition largely contributing to this matter is syncope, which has an economic impact equivalent to conditions such as asthma, HIV, and chronic obstructive pulmonary disease. More commonly known as fainting, syncope is associated with high rate of falls and hospitalization and is responsible for reducing lifestyle quality, especially in the elderly. To face this socioeconomic burden caused by CVDs, the health care paradigm is shifting from a reactive hospital-centered to a preventive individual-centered care, with special emphasis in earlier diagnosis and better prevention and management strategies. Therefore, the development of new methodologies for monitoring the cardiovascular function, capable of being applied in low-cost, non-invasive and portable systems, are essential to prevent and control the evolving epidemic of CVDs. Despite the recent technological advances, the current standard techniques for the assessment of cardiovascular function, such as the cardiac magnetic resonance and echocardiography, still exhibit several limitations in what concerns to their application in personal health environments. Therefore, the use of widely available and cost-effective modalities such as the electrocardiogram and photoplethysmogram, for the non-invasive, continuous and long-term assessment of the cardiovascular function may be the key to provide a better prevention and management strategies of CVDs. More specifically, the extraction of cardiovascular parameters from these modalities may be crucial in the prediction of syncope events and prevention of falls. The key contribution of the present thesis is the development of new algorithms for the continuous, non-invasive and robust assessment of cardiovascular function, based on the analysis of the electrocardiogram and photoplethysmogram. Since the photoplethysmogram is easily influenced by noise and motion artifacts, which can be a serious obstacle in the extraction of cardiovascular parameters, it is essential to detect which sections of the photoplethysmogram are liable for further analysis. Therefore, we propose a new method for the detection of motion artifacts, based on the extraction and analysis of time and period domain features. Consequently, we propose a new algorithm for the assessment of the left ventricular ejection time, which is associated with the cardiac function, among other parameters related with blood pressure and vascular tones changes. Finally, we propose a new algorithm for the prediction of syncope events (more specifically, neurally mediated syncope), based on the evaluation of changes in the previously extracted cardiovascular parameters. The proposed methods were validated in three databases collected in the Department of Informatics Engineering of the University of Coimbra, in the Hospital Center of University of Coimbra and in the Department of Electrophysiology of the University Heart Center, University Hospital Eppendorf, Hamburg, Germany.

博士
國立中興大學
環境工程學系
92
This study contains two major parts. Part 1 focused on the sampling artifacts of nitric acid gas by using annular denuder system (ADS). A theoretical model was developed in this part to evaluate the theoretical sampling artifact. Four denuder tubes coated with the same NaCl adsorption in an annular denuder system was also applied in the field experiment to evaluate the positive and negative errors. Part 2 concentrated on the characteristic (including gaseous and particulate concentrations and size distribution) of ambient air polycyclic aromatic hydrocarbon (PAH) and its health risk assessment in different sampling sites of central Taiwan. The result of theoretical model indicated that the sampling artifact of nitric acid gas was more serious under situation of higher ambient temperature, higher inlet particle number concentration, larger inlet particle diameter, higher nitrate concentration in diameter less than 2.5 m particle and lower inlet nitric acid gas concentration. Field study was conducted to evaluate degrees of positive and negative errors as well as possible error sources of one NaCl-denuder system for HNO3 measurement. The results indicated that both negative error and positive error could simultaneously exist, but they might cancel each other and lead to less remarkable overall error concentrations. The negative errors could be important for sampling relatively low HNO3 concentrations or at high ambient temperatures. On the other hand, the positive errors could be due to both N-containing gases and nitrate particles. This study also intended to quantitatively determine the contribution of positive error from either particle phase (evaporation error and diffusion error) or gas phase (N-gas error). The result indicated that the evaporation, diffusion and N-gas error was 77 %, 9 % and 14 %, respectively to the total positive error. The nitrate concentration in less than 2.5 m particles and the true HNO3 gas concentration were the key factors that influence the degree of evaporation error. High values of these two factors could cause significant error concentrations and must be avoided in the field measurement of atmospheric HNO3 gas by a denuder system. The particulate total PAH concentration was 93.4, 81.3 and 102.4 ng/m3 in the urban, rural and industrial sampling site, respectively. The gaseous total PAH concentration was 1030, 758 and 1530 ng/m3 in the urban, rural and industrial sampling site, respectively. The result indicated that the influence of gaseous PAH was more serious than the particulate PAH in central Taiwan. 2-4 rings PAH contributed about 95 % of total gaseous PAH and medium molecular weight PAH (5-6 rings) occupied about 50 % in the total particulate PAH. The gaseous PAHs in central Taiwan carcinogenic activity can be explained by individual BaP concentration because it is high percentage of carcinogenicity to the total carcinogenic activity. The 21 particle-bound PAHs concentrations were 118, 75.3 and 115 ng/m3 for industrial, rural and urban, respectively. For carcinogenic activity of particle-bound PAHs, the BaP equivalent concentrations were 4.24, 8.97 and 4.56 ng/m3 for industrial, rural and urban, respectively.

abstract: Eat Your Heart Out is a visually rich qualitative ethnic food research that examines consumption, production, and distribution practices transnationally. Through the example of Mumbai’s street foods, the study aims to discover how design participates in fashioning the street food experiences locally and globally. Food is an important cultural artifact in the world. However, past research in design suggests that the discipline has mainly focused on food as a catalyst for creativity and imagination or as a tool to examine materialistic, economical, sensorial, and emotional connections. Studying the user-focused involvement in the creation of food artifacts and focusing on cultural, global, and historical aspects of that participation are important to address the gaps in the knowledge required to solve increasingly “wicked problems” (Buchanan, 1992; Rittel, 1971). To achieve this goal, Eat Your Heart Out implemented a comparative practice-based study of the Indian street foods in Mumbai and Phoenix to examine consumption, production, and distribution practices at both places. The methodological design was highly multi-disciplinary in nature and included rapid ethnographic assessment, interviews, visual research, and a generative method of co-creation. The study revealed that street foods as cultural artifacts were deeply rooted in specific traditional values specific to the context, which significantly influenced personal and communal consumption, production, and distribution practices of Indian street foods in Mumbai and Phoenix. The values of standardization, formality, and higher food regulation practices limited the diversity and radically transformed the central values of Mumbai’s street foods when the foods re-territorialized in Phoenix. This resulted in lowering the consumption. Eat Your Heart Out presents cultural and practical insights into the interactions between contexts, artifacts, practices, and participants. Eat Your Heart Out recommends new frameworks of correlation for various consumption and production practices and suggests how street food artifacts alter when they move across cultures. Such knowledge can be valuable for similar ethnic food culture studies and the development of innovative research tools incorporating transnational and multidisciplinary methods in the future. On a broader scope, Eat Your Heart Out provides a unique opportunity to study a culture that has not been examined by scholars much in the past. It also focuses on gaining knowledge about ethnic culinary practices of Indian immigrants in the United States and encouraging enhanced cross-cultural acceptance.
Dissertation/Thesis
Doctoral Dissertation Design, Environment and the Arts 2018

Physiological signals, electroencephalogram (EEG) and heart rate variability (HRV), are generated by complex self-regulating systems. These signals are extremely inhomogeneous and nonstationary, and fluctuate in an irregular and highly complex manner. These fluctuations are due to underlying dynamics of the system. The synchronous neural activity measured as scalp EEG indicates underlying neural dynamics of the brain. Hence, quantitative EEG analysis has become a very useful tool in interpreting results from physiological experiments. The analysis of HRV provides valuable information to assess the autonomous nervous system (ANS). The HRV can be significantly affected by physiological state changes and many disease states. Hence, HRV analysis is becoming a major experimental and diagnostic tool. In this thesis, we focus on the study of EEG and HRV time series using tools from nonlinear time series analysis with special emphasis on its implications in detecting physiological state changes such as, in diseases like epileptic seizure and schizophrenia, and in altered states of consciousness as in sleep and meditation. The proposed nonlinear techniques are used in discriminating different physiological states from control states. Artifact processing of EEG signal Interferences (artifacts) from various sources unavoidably contaminate EEG recordings. In quantitative analysis, results can differ significantly by these artifacts, which may lead to wrong interpretation of the results. In this part of the thesis, we have devised methods to minimize ocular and muscle artifacts in EEG. The artifact correction methods are based on blind source separation (BSS) techniques such as singular value decomposition (SVD), algorithm for multiple signal extraction (AMUSE), canonical correlation analysis (CCA), information maximization (INFOMAX) independent component analysis (ICA) and joint approximate diagonalization of eigen-matrices (JADE) ICA. We have proposed a method to simulate clean and artifact corrupted EEG data based on the BSS methods. In order to enhance the performance of BSS methods, a technique called wavelet-filtered component inclusion method has been introduced. In addition, second-order statistics (SOS) and higher-order statistics (HOS) based BSS methods have been studied considering less number of EEG channels; and performance comparison of these methods has also been made. We have also addressed the problem of simultaneous correction of ocular and muscle artifacts in EEG recordings using the BSS methods. Irrespective of the BSS methods, the component elimination method has introduced high spectral error in all the bands after reconstruction of clean EEG. However, the wavelet filtered component inclusion method has retained almost all spectral powers of EEG channels in theta, alpha, and beta bands after ocular artifact minimization. When the number of EEG channels is very less, the enhanced CCA (SOS BSS) has given superior artifact minimization results than HOS BSS methods, especially in delta band. The component elimination method is used in muscle artifact minimization, and hence the SVD method cannot be used for this purpose since it leads to large spectral distortion of reconstructed EEG. The AMUSE and CCA methods have given comparable performance in muscle artifact minimization. In addition, the JADE method has introduced less mean spectral error compared to other methods. The CCA method has shown superior performance in simultaneous minimization of ocular and muscle artifacts, and AMUSE and JADE methods have given comparable results. Furthermore, the less computation time of wavelet enhanced SOS BSS methods make them very useful in real clinical environments. Fractal characterization of time series In biomedical signal analysis, fractal dimension (FD) is used as a quantitative measure to estimate complexity of physiological signals. Such analysis helps to study physiological processes of underlying systems. The FD can also be used to study dynamics of transitions between different states of systems like brain and ANS, in various physiological and pathological states. In this part, we have proposed a method to estimate FD of time series, called multiresolution box-counting (MRBC) method. A modification of this method resulted in multiresolution length (MRL) method. The estimation performance of the proposed methods is compared with that of Katz, Sevcik, and Higuchi methods, by simulating mathematically defined fractal signals, and also the computation time is compared between the methods. The MRBC and MRL methods have given comparable performance to that of Higuchi method, in estimating FD of waveforms, with the advantage of less computational time. In addition, various properties of the FD are studied and discussed in connection with classical signal processing concepts such as amplitude, frequency, sampling frequency, effect of noise, band width, correlation, etc. The FD value of signals has increased with number of harmonics, noise variance, band-width, and mid-band frequency, and decreased with degree of correlation in AR signal. An analogy between Katz FD and smoothed Teager energy operator has also been made. Application of fractal analysis to EEG and HRV time series The fluctuation of EEG potentials normally depends upon degree of alertness, and varies in amplitude and frequency. Hence, the EEG is an important clinical tool for studying sleep and sleep related disorders, epileptic seizures, schizophrenia, and meditation. In this part of the thesis, we have used FD which gives signal complexity, and detrended fluctuation analysis (DFA) which gives multiscale exponent of time series to quantify EEG. We have extended the concept of FD to multiscale FD to compute complexity of time series at multiple scales. The main applications of the proposed method are epileptic seizure detection, sleep stage detection, schizophrenia EEG analysis, and analysis of heart rate variability during meditation. For seizure detection, we have used intracranial EEG recordings with seizure-free and seizure intervals. In sleep EEG analysis, whole-night sleep EEG is used and results are compared with the manually scored hypnogram. The schizophrenia symptom is further categorized into positive and negative symptoms and complexity is estimated using FD and DFA. We have also analyzed HRV data of Chi and Kundalini meditation using FD and DFA techniques. In all the applications considered, we have tested for statistical significance of the computed parameters, between the case of interest and corresponding control cases, to discriminate between the physiological states. The ocular artifact has reduced FD while muscle artifact increased FD of EEG. The FD of seizure EEG has shown high value compared to that of seizure-free EEG. In addition, the seizure-free EEG has more DFA exponent-1 than seizure EEG. The value of FD of EEG is decreased with deepening of sleep, wake state having high FD value. The FD of REM state sleep EEG showed value between that of wake and state-1. The DFA exponent-1 has increased with deepening of sleep state, having small value for wake state. The REM state has given exponent-1 value between wake and state-1. The schizophrenia subjects have shown lower FD value than healthy controls in all the EEG channels except the bilateral temporal and occipital regions. The positive symptom sub-group has shown comparatively high FD values than healthy controls as well as overall schizophrenia sample in the bilateral tempero-parietal-occipital region. In addition, the positive symptom sub-group has shown significantly higher regional FD values than negative symptom sub-group especially in right temporal region. The overall schizophrenia samples as well as the positive and negative subgroup have shown least FD values in the bilateral frontal region. The values of DFA exponent-2 have shown significant high value in schizophrenia samples. In addition, the schizophrenia group has shown less DFA exponent-1 in bilateral temporal region than healthy control. The FD, multiscale FD, DFA exponents have shown significant performance in discriminating different physiological states from control states. The FD value of HRV time series during meditation is less compared to pre-meditation state in both Chi and Kundalini meditation. Irrespective of the type of meditation, meditation state has shown significantly high DFA exponent-1 than pre-meditation state, and significantly high DFA exponent-2 in pre-meditation state compared to meditation state. Functional connectivity analysis of brain during meditation In functionally related regions of the brain, even in those regions separated by substantial distances, the EEG fluctuations are synchronous, which is termed as functional connectivity. In this part, a novel application of functional connectivity analysis of brain using graph theoretic approach has been made on the EEG recorded from meditation practitioners. We have used 16 channel EEG data from subjects while performing Raja Yoga meditation. The pre-meditation condition is used as control state, against which meditation state is compared. For finding connectivity between EEG of various channels, we have computed pair-wise linear correlation and mutual information between the EEG channels, to form a connection matrix of size 16x16. Then, various graph parameters, such as average connection density, degree of nodes, characteristic path length, and cluster index, are computed from the connection matrix. The computed parameters are projected on to the scalp to get topographic head maps that give spatial variation of the parameter, and results are compared between meditation and pre-meditation states. The meditation state has shown low average connection density, less characteristic path length, and high average degree in fronto-central and central regions. Furthermore, high cluster index is shown in frontal and central regions than pre-meditation state. The parameters such as complexity, characteristic path length and average connection density are used as features in quadratic discriminant classifier to classify meditation and pre-meditation state, and have given good accuracy performance. Connectivity analysis using mutual information has given high average connection density in meditation state in theta, alpha and beta bands compared to pre-meditation state. The characteristic path length is high in delta, alpha and beta bands in meditation state. In addition, the meditation state has shown high degree and cluster index in theta and beta bands compared to pre-meditation state. Nonlinear dynamical characterization of HRV during meditation The cardiovascular system is influenced by internal dynamics as well as from various external factors, which makes the system more dynamic and nonlinear. In this part of the thesis, a novel application of using HRV data for studying Chi and Kundalini meditation has been made. The HRV time series are embedded into higher dimensional phase-space using Takens’ embedding theorem to reconstruct the attractor. After estimating the minimum embedding dimension to unfold the attractor dynamics, the complexity of the attractor is computed using correlation dimension, Lyapunov exponent, and nonlinearity scores. In all the analyses, the pre-meditation state is used as control state against which meditation state is compared. The statistical significance of the parameters estimated is tested to discriminate meditation state from control state. The HRV time series of both pre-meditation and meditation have shown similar minimum embedding dimensions in both Chi and Kundalini meditation. Irrespective of the type of meditation, the meditation state has shown high correlation dimension, largest Lyapunov exponent, and low nonlinearity score compared to pre-meditation state. Recurrent quantification analysis of HRV during meditation In this part, a novel application of recurrent quantification analysis (RQA) to HRV during meditation is studied. Here, the time series is embedded into a higher dimensional phase-space and Euclidean distance between the embedded vectors is calculated to form a distance matrix. The matrix is converted into binary matrix by applying a suitable threshold, and plotted as image to get recurrence plot. Various parameters are extracted from the recurrence plot such as percent recurrence rate, diagonal parameters (determinism, divergence, entropy, ratio), and vertical or horizontal parameters (laminarity, trapping time, maximal vertical line length). The procedure is applied to HRV data during meditation and pre-meditation (control) to discriminate between the states. The HRV of meditation state has shown more diagonal line structure whereas more black patches are observed in pre-meditation state. In addition, at low embedding dimensions, the meditation state has shown low recurrence rate, high determinism, low divergence, low entropy, high ratio, high laminarity, high trapping time, and less maximal vertical line length compared to pre-meditation state. These RQA parameters have shown superior performance in discriminating meditation state from control state.