Relevant bibliographies by topics / Plethysmography Signal Processing

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Plethysmography Signal Processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Plethysmography Signal Processing"

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Sasono, Margi, and Apik Rusdiarna Ip. "A Portable and USB-Powered Device for Heart Rate Extraction of Optical Plethysmography Signal." Applied Mechanics and Materials 771 (July 2015): 13–16. http://dx.doi.org/10.4028/www.scientific.net/amm.771.13.

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Optical plethysmography technology has been used to design and develop a portable device for heart rate sensor. These device, consisting of near-infrared light-emitting diodes (LEDs) and photodetectors, offer a simple means of extraction the heart rate noninvasively on fingertip’s healthy volunteers. The acquisition signal is carried out based on the detection of the absorbance of near-infrared light in blood vessels due to heart’s pump activity. The microcontroller is used as the main component of electronics module. The communication to personal computer (PC) and power supply of device are provided by USB system. The algorithm of Fast Fourier Transform (FFT) in the software was used to generate the spectra of the signal and determine the HR of the obtained signal. The performance of developed device is tested on 10 fingertips of healthy volunteers, aged 19 to 57 years. A Pulse Oximeter commercial was used as gold standard instrument for comparison of results obtained by the designed device. In this paper the correlation analysis was applied to validate the results of both devices. The analysis show that the HR measured is positively correlated. These results show that the correlation between the HR measured by both the designed PPG device and Pulse Oximeter commercial are almost perfectly linear. Thus, the pulse signals gathered by the designed device are accurately believed to be representative of the heart activity of healthy volunteers. The validation method supports that designed device can potentially be developed as a simple, low power, and portable device for the importance of biomedical research (mainly for processing biomedical signal) and clinical practices.
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Georgieva-Tsaneva, Galya, Evgeniya Gospodinova, Mitko Gospodinov, and Krasimir Cheshmedzhiev. "Portable Sensor System for Registration, Processing and Mathematical Analysis of PPG Signals." Applied Sciences 10, no. 3 (February 5, 2020): 1051. http://dx.doi.org/10.3390/app10031051.

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This article introduces an integrated photoplethysmographic (PPG) based cardiovascular monitoring system that consists of an individually portable PPG device for recording photoplethysmographic signals and a software system with a serverless architecture for processing, storing, and analyzing the obtained signals. The portable device uses the optical plethysmography technique for measuring blood volume in blood vessels. The device was tested and validated by a comparative analysis of three photoplethysmographic signals and one Electrocardiographic signal registered simultaneously in the target subject. The comparative analysis of these signals shows insignificant deviations in the obtained results, with the mean squared error between the studied signals being less than 21 ms. This deviation cannot affect the results that were obtained from the analysis of the interval series tested. Based on this result, we assume that the detected signals with the proposed device are realistic. The designed software system processes the registered data, performs preprocessing, determines the pulse rate variability, and performs mathematical analysis of PP intervals. Two groups of subjects were studied: 42 patients with arrhythmia and 40 healthy controls. Mathematical methods for data analysis in time and frequency domain and nonlinear methods (Poincaré plots, Rescaled Range Plot, Detrended Fluctuation Analysis, and MultiFractal Detrended Fluctuation Analysis) are applied. The obtained results are presented in tabular form and some of them in graphical form. The parameters studied in the time and frequency domain, as well as with the nonlinear methods, have statistical significance (p < 0.05) and they can distinguish between the two studied groups. Visual analysis of PP intervals, based on Poincare’s nonlinear method, provides important information on the physiological status of patients, allowing for one to see at a glance the entire PP interval series and quickly detect cardiovascular disorders, if any. The photoplethysmographic data of healthy individuals and patients diagnosed with arrhythmia were recorded, processed, and examined through the system under the guidance of a cardiologist. The results were analyzed and it was concluded that this system could serve to monitor patients with cardiovascular diseases and, when the condition worsens, a signal could be generated and sent to the hospital for undertaking immediate measures to stabilize patient’s health.
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Pielmus, Alexandru-Gabriel, Michael Klum, Timo Tigges, Reinhold Orglmeister, and Mike Urban. "Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation." Current Directions in Biomedical Engineering 6, no. 3 (September 1, 2020): 579–82. http://dx.doi.org/10.1515/cdbme-2020-3148.

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AbstractArterial blood pressure is one of the most important cardiovascular parameters. Yet, current-generation devices for continuous, noninvasive acquisition are few, expensive and bulky. Novel signal processing applied to easily acquired unimodal signals can alleviate this issue, reducing size, cost and expanding the use of such devices to ambulatory, everyday settings. The features of pulse waves acquired by photo- or impedance-plethysmography can be used to estimate the underlying blood pressure. We present a progressive dynamic time warping algorithm, which implicitly parametrizes the morphological changes in these waves. This warping method is universally applicable to most pulse wave shapes, as it is largely independent of fiducial point detection or explicit parametrization. The algorithm performance is validated in a feature selection and regression framework against a continuous, noninvasive Finapres NOVA monitor, regarding systolic, mean and diastolic pressures during a light physical strain test protocol on four clinically healthy subjects (age18- 33, one female). The obtained mean error is 2.13 mmHg, the mean absolute error is 5.4 mmHg and the standard deviation is 5.6 mmHg. These results improve on our previous work on dynamic time warping. Using single-sensor, peripherally acquired pulse waves, progressive dynamic time warping can thus improve the flexibility of noninvasive, continuous blood pressure estimation.
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Cesareo, Ambra, Ylenia Previtali, Emilia Biffi, and Andrea Aliverti. "Assessment of Breathing Parameters Using an Inertial Measurement Unit (IMU)-Based System." Sensors 19, no. 1 (December 27, 2018): 88. http://dx.doi.org/10.3390/s19010088.

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Breathing frequency (fB) is an important vital sign that—if appropriately monitored—may help to predict clinical adverse events. Inertial sensors open the door to the development of low-cost, wearable, and easy-to-use breathing-monitoring systems. The present paper proposes a new posture-independent processing algorithm for breath-by-breath extraction of breathing temporal parameters from chest-wall inclination change signals measured using inertial measurement units. An important step of the processing algorithm is dimension reduction (DR) that allows the extraction of a single respiratory signal starting from 4-component quaternion data. Three different DR methods are proposed and compared in terms of accuracy of breathing temporal parameter estimation, in a group of healthy subjects, considering different breathing patterns and different postures; optoelectronic plethysmography was used as reference system. In this study, we found that the method based on PCA-fusion of the four quaternion components provided the best fB estimation performance in terms of mean absolute errors (<2 breaths/min), correlation (r > 0.963) and Bland–Altman Analysis, outperforming the other two methods, based on the selection of a single quaternion component, identified on the basis of spectral analysis; particularly, in supine position, results provided by PCA-based method were even better than those obtained with the ideal quaternion component, determined a posteriori as the one providing the minimum estimation error. The proposed algorithm and system were able to successfully reconstruct the respiration-induced movement, and to accurately determine the respiratory rate in an automatic, position-independent manner.
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Haseda, Yuki, Julien Bonefacino, Hwa-Yaw Tam, Shun Chino, Shouhei Koyama, and Hiroaki Ishizawa. "Measurement of Pulse Wave Signals and Blood Pressure by a Plastic Optical Fiber FBG Sensor." Sensors 19, no. 23 (November 21, 2019): 5088. http://dx.doi.org/10.3390/s19235088.

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Fiber Bragg grating (FBG) sensors fabricated in silica optical fiber (Silica-FBG) have been used to measure the strain of human arteries as pulse wave signals. A variety of vital signs including blood pressure can be derived from these signals. However, silica optical fiber presents a safety risk because it is easily fractured. In this research, an FBG sensor fabricated in plastic optical fiber (POF-FBG) was employed to resolve this problem. Pulse wave signals were measured by POF-FBG and silica-FBG sensors for four subjects. After signal processing, a calibration curve was constructed by partial least squares regression, then blood pressure was calculated from the calibration curve. As a result, the POF-FBG sensor could measure the pulse wave signals with an signal to noise (SN) ratio at least eight times higher than the silica-FBG sensor. Further, the measured signals were substantially similar to those of an acceleration plethysmograph (APG). Blood pressure is measured with low error, but the POF-FBG APG correlation is distributed from 0.54 to 0.72, which is not as high as desired. Based on these results, pulse wave signals should be measured under a wide range of reference blood pressures to confirm the reliability of blood pressure measurement uses POF-FBG sensors.
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Cobos-Torres, Juan-Carlos, Mohamed Abderrahim, and José Martínez-Orgado. "Non-Contact, Simple Neonatal Monitoring by Photoplethysmography." Sensors 18, no. 12 (December 10, 2018): 4362. http://dx.doi.org/10.3390/s18124362.

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This paper presents non-contact vital sign monitoring in neonates, based on image processing, where a standard color camera captures the plethysmographic signal and the heart and breathing rates are processed and estimated online. It is important that the measurements are taken in a non-invasive manner, which is imperceptible to the patient. Currently, many methods have been proposed for non-contact measurement. However, to the best of the authors’ knowledge, it has not been possible to identify methods with low computational costs and a high tolerance to artifacts. With the aim of improving contactless measurement results, the proposed method based on the computer vision technique is enhanced to overcome the mentioned drawbacks. The camera is attached to an incubator in the Neonatal Intensive Care Unit and a single area in the neonate’s diaphragm is monitored. Several factors are considered in the stages of image acquisition, as well as in the plethysmographic signal formation, pre-filtering and filtering. The pre-filter step uses numerical analysis techniques to reduce the signal offset. The proposed method decouples the breath rate from the frequency of sinus arrhythmia. This separation makes it possible to analyze independently any cardiac and respiratory dysrhythmias. Nine newborns were monitored with our proposed method. A Bland-Altman analysis of the data shows a close correlation of the heart rates measured with the two approaches (correlation coefficient of 0.94 for heart rate (HR) and 0.86 for breath rate (BR)) with an uncertainty of 4.2 bpm for HR and 4.9 for BR (k = 1). The comparison of our method and another non-contact method considered as a standard independent component analysis (ICA) showed lower central processing unit (CPU) usage for our method (75% less CPU usage).
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Lu, Xinyue, Christine Azevedo Coste, Marie-Cécile Nierat, Serge Renaux, Thomas Similowski, and David Guiraud. "Respiratory Monitoring Based on Tracheal Sounds: Continuous Time-Frequency Processing of the Phonospirogram Combined with Phonocardiogram-Derived Respiration." Sensors 21, no. 1 (December 25, 2020): 99. http://dx.doi.org/10.3390/s21010099.

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Patients with central respiratory paralysis can benefit from diaphragm pacing to restore respiratory function. However, it would be important to develop a continuous respiratory monitoring method to alert on apnea occurrence, in order to improve the efficiency and safety of the pacing system. In this study, we present a preliminary validation of an acoustic apnea detection method on healthy subjects data. Thirteen healthy participants performed one session of two 2-min recordings, including a voluntary respiratory pause. The recordings were post-processed by combining temporal and frequency detection domains, and a new method was proposed—Phonocardiogram-Derived Respiration (PDR). The detection results were compared to synchronized pneumotachograph, electrocardiogram (ECG), and abdominal strap (plethysmograph) signals. The proposed method reached an apnea detection rate of 92.3%, with 99.36% specificity, 85.27% sensitivity, and 91.49% accuracy. PDR method showed a good correlation of 0.77 with ECG-Derived Respiration (EDR). The comparison of R-R intervals and S-S intervals also indicated a good correlation of 0.89. The performance of this respiratory detection algorithm meets the minimal requirements to make it usable in a real situation. Noises from the participant by speaking or from the environment had little influence on the detection result, as well as body position. The high correlation between PDR and EDR indicates the feasibility of monitoring respiration with PDR.
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Rodrigues, Kessiler Almeida Silveira, Moisés Henrique Ramos Pereira, and Flávio Luis Cardeal Pádua. "DETECÇÃO EM TEMPO REAL DA FREQUÊNCIA CARDÍACA DE PESSOAS POR MEIO DA ANÁLISE DE VARIAÇÕES TEMPORAIS EM VÍDEOS." e-xacta 9, no. 1 (June 1, 2016): 49. http://dx.doi.org/10.18674/exacta.v9i1.1666.

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<p>As doenças cardiovasculares são, atualmente, as causas mais comuns de morbimortalidade no mundo. Na perspectiva da prevenção de doenças e agravos, tornam-se fundamentais ações que criem ambientes favoráveis à saúde e favoreçam escolhas saudáveis. Medidas de prevenção e monitoramento contínuo de sinais vitais são necessários, sendo a frequência cardíaca um sinal promissor. No entanto, tal monitoramento pode ser difícil e pouco eficiente, quando não impossível, em determinados casos, como por exemplo, vítimas de queimaduras. Este artigo propõe uma aplicação para monitoramento da frequência cardíaca não invasivo e sem a necessidade de contato, podendo ser manuseado por qualquer pessoa. Para a determinação da frequência cardíaca, a aplicação combina técnicas de processamento de imagens, tratamento de sinais fotopletismográficos e análise de variações temporais em vídeos. Os resultados obtidos demonstram que, considerando 95% de confiança estatística e um erro padrão de 1,08 batimentos por minuto, a aplicação desenvolvida possui a mesma média para aferições de batimentos cardíacos em relação a um dispositivo já consolidado no mercado para essa finalidade, mostrando-se como um método computacional promissor para medições em repouso.</p><p>Abstract </p><p>Cardiovascular diseases are currently the most common causes of morbidity and mortality worldwide. From the perspective of prevention of diseases and disorders, become fundamental actions that create supportive environments for health and promote healthy choices. Prevention and continuous monitoring of vital signs are necessary, and the heart rate a promising sign. However, such monitoring can be difficult and inefficient, if not impossible, in certain cases, such as burn victims. This paper proposes an application for monitoring heart rate non-invasive and without the need to touch and can be handled by anyone. For the determination of heart rate the application combines techniques of image processing, processing and analysis of signals photo-plethysmography temporal changes in video. The obtained results show that, considering a 95% statistical confidence and a standard error of 1.08 beats per minute, the developed application has the same average heartbeats' measurements in relation to a consolidated device on the market used for the same purpose, showing itself as a promising computational method for rest measurements.</p>
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Margi Sasono and Apik Rusdiarna Indrapraja. "Computerized Optical Plethysmography for Data Recording and Processing of Biomedical Signal." International Journal of Engineering Research and V5, no. 02 (February 27, 2016). http://dx.doi.org/10.17577/ijertv5is020608.

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"Non-Contact Pulse Detector using Video Analytics." International Journal of Innovative Technology and Exploring Engineering 9, no. 5 (March 10, 2020): 1597–600. http://dx.doi.org/10.35940/ijitee.d2051.039520.

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Non-contact pulse detector used for heart beat measurement based on computer vision, where a standard color camera captures the plethysmographic signal and the heart rates are processed and estimated dynamically. It is important that the quantities are taken in a non-invasive manner, which is invisible to the patient. Presently, many methods have been proposed for non-contact measurement. The proposed method based on the computer vision technique is enhanced to overcome the above drawbacks and it requires low computational cost. Many of the hospitals are using surveillance cameras, from these cameras we can monitor the video of the patients waiting in the queue. The camera is attached in the patients’ waiting room and the faces of the patients are monitored. Many factors are considered in the phases of image acquisition, as well as in the plethysmographic signal development, pre-processing and filtering. The pre-filter step uses numerical analysis techniques to cut the signal offset. The proposed method decouples the heart rate from the plethysmographic signal frequency. The proposed system helps in detecting the heart rate of a Patient who is waiting in queue for longer time. Based on the heart rate the seriousness of patient is identified and giving the preference to the patient and treatment will be started, with this the patient will be in safe side.
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Dissertations / Theses on the topic "Plethysmography Signal Processing"

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Huang, Lingyun. "Ultrasound plethysmography : signal processing and application /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/8057.

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Hutchinson, Reginald C. 1976. "Design and signal processing of finger photo plethysmograph ring sensors for reduced motion artifact and circulation interference." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/89355.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
Includes bibliographical references (leaves 108-111).
by Reginald C. Hutchinson.
S.M.
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Porras, Desiderio Cano. "Comparação da assincronia toracoabdominal ao repouso e ao exercício em pacientes com doença pulmonar obstrutiva crônica utilizando diferentes metodologias." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/5/5170/tde-27082014-091225/.

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Pacientes portadores de doença pulmonar obstrutiva crônica (DPOC) podem apresentar assincronia toracoabdominal (ATA). Existem diversos métodos de estimativa da ATA, porém, não há um consenso sobre qual é o mais adequado. O objetivo deste estudo foi comparar dois métodos de estimativa da assincronia toracoabdominal e avaliar a ineficiência ventilatória em pacientes DPOC no repouso e durante o exercício. Foram avaliados 22 pacientes com DPOC (VEF1 40,2±10,5% predito) e 13 indivíduos controle (GC) pareados por idade, gênero e índice de massa corpórea. A cinemática toracoabdominal foi avaliada utilizando pletismografia optoeletrônica no repouso e durante o exercício leve e moderado (70% da carga máxima) no ciclo ergômetro. A ATA foi calculada entre a caixa torácica superior (CTS) e inferior (CTI) e o abdome (ABD) utilizando os métodos de ângulo de fase (AF) e relação de fase (RF). A ineficiência ventilatória foi calculada em cada compartimento como a diferença entre o volume máximo (VM) e o volume calculado (VC) de acordo com o ciclo respiratório (determinado pela soma de volume dos três compartimentos) dividida pelo volume máximo (VM-VC)/VM. Os pacientes com DPOC foram classificados como assíncronos (grupo AT) ou não assíncronos (grupo NA) utilizando como referência os valores do GC. Foi utilizado o teste qui-quadrado ou de Fisher para avaliar a discriminação de pacientes entre os métodos e o ANOVA de dois fatores para comparações entre os grupos. O nível de significância foi ajustado para 5%. O método AF determinou maior número de pacientes com ATA quando comparado com RF no repouso (respectivamente, 15 vs. 7) e no exercício leve (11 vs. 3) e moderado (14 vs. 8). Os valores de assincronia no grupo AT entre CTS-CTI e CTI-ABD foram maiores no repouso (AF: 35,7±45,4° e -42,2±42,5° e RF: 61,8±29,1° e -66,9±27,4°, respectivamente) e no exercício leve (AF: 53,3±35,6° e -55,8±40,4°; RF: 106,1±40,3° e - 124,8±17,2°) e moderado (AF: 61,6±55,1° e -75,9±44,8°; RF: 85,9±23,6° e -81,8±42,2°) quando comparados com os grupos NA (p < 0,05) e GC (p < 0,05). Na análise entre CTSABD não houve diferença entre os grupos. Observou-se que o grupo AT apresentou menor contribuição e maior ineficiência ventilatória da CTI em todos os momentos de avaliação e, durante o exercício moderado, menor volume corrente quando comparado com os grupos NA e GC. Os nossos resultados sugerem que o ângulo de fase apresenta maior detecção de ATA nos pacientes com DPOC. A presença de assincronia parece ocorrer principalmente na caixa torácica inferior e associada com menor contribuição e maior ineficiência ventilatória deste compartimento
Chronic obstructive pulmonary disease (COPD) patients can present thoracoabdominal asynchrony (TAA). There are several TAA estimation techniques, however, there is no consensus about which is the most appropriate. The aim of this study was to compare two thoracoabdominal asynchrony quantification techniques and to assess chest wall ventilatory inefficiency in COPD patients at rest and during exercise. We evaluated 22 COPD patients (FEV1 40,2±10,5% predicted) and 13 healthy controls (CG) matched by age, gender and body mass index. Thoracoabdominal kinematics was assessed via optoelectronic plethysmography at rest and during mild and moderate exercise (70 % maximum workload) in a cycle ergometer. TAA was calculated among upper (URC) and lower ribcage (LRC) and abdomen (ABD) by using the phase angle (PA) and phase relation (PR) approaches. Ventilatory Inefficiency was estimated in each compartment as the difference between the maximal volume (VM) and the volume (VC) calculated according to respiratory timing (sum of volume in the 3 compartments) divided by the maximal volume (VM-VC)/VM. COPD patients were classified as asynchronous (AT group) or not (NA group) by using as reference the values on the controls. Chi-square or Fisher\'s exact test was used for assessing the patients differentiation between the two TAA quantification approaches and two-way ANOVA was used to compare respiratory parameters among groups (CG, AT and NA). Statistical significance was set at 5% level. PA approach determined more patients as asynchronous when compared to RF at rest (respectively, 15 vs. 7) and during mild (11 vs. 3) and moderate (14 vs. 8) exercise. Asynchrony values in AT group among URC-LRC and LRC-ABD were greater at rest (respectively, 35.7±45.4° and -42.2±42.5° with PA and 61.8±29.1° and -66.9±27.4° with PR) and during mild (PA: 53.3±35.6° and -55.8±40.4°; PR: 106.1±40.3° and -124.8±17.2°) and moderate exercise (PA: 61.6±55.1° and - 75.9±44.8°; PR: 85.9±23.6° and -81.8±42.2°) when compared to NA (p < 0.05) and CG (p < 0.05). Analysis among URC-ABD presented no difference between groups. It was observed that AT group presented a smaller LRC contribution and greater ventilatory inefficiency during all assessing moments and, during moderate exercise, had a lower tidal volume when compared to NA and CG. Our results suggest that phase angle approach presents larger TAA detection in COPD patients. This asynchrony seems to occur mainly in the lower ribcage and be associated with decreased contribution and increased ventilatory inefficiency of this compartment
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Book chapters on the topic "Plethysmography Signal Processing"

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Maletras, F. X., A. T. Augousti, and J. Mason. "Signal Processing Considerations in the use of the Fibre Optic Respiratory Plethysmograph (FORP) for Cardiac Monitoring." In Sensors and their Applications XI, 371–76. CRC Press, 2018. http://dx.doi.org/10.1201/9781351076593-56.

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Conference papers on the topic "Plethysmography Signal Processing"

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Prauzek, Michal, Tomas Peterek, Ondrej Adamec, and Marek Penhaker. "Analog signal preprocessing in reflected Plethysmography." In 2010 2nd International Conference on Signal Processing Systems (ICSPS). IEEE, 2010. http://dx.doi.org/10.1109/icsps.2010.5555637.

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More, S., and P. Choudhari. "Developement of Classification Indices for Diseases using Photo Plethysmography." In International Conference on Communication and Signal Processing 2016 (ICCASP 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/iccasp-16.2017.70.

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More, Shamali V., and Pranali C. Chaudhari. "Development of non-invasive diagnostic tool for diseases using Photo Plethysmography." In 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, 2016. http://dx.doi.org/10.1109/wispnet.2016.7566387.

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Cambara, Guillermo, Jordi Luque, and Mireia Farrus. "Detection of Speech Events and Speaker Characteristics through Photo-Plethysmographic Signal Neural Processing." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9052972.

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"Changes in the Spectral Characteristics of Plethysmographic Waveforms Due to PAOD." In International Conference on Bio-inspired Systems and Signal Processing. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004747301490154.

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Karamchandani, S. H., M. Panju, H. D. Mustafa, S. N. Merchant, U. B. Desai, and G. D. Jindal. "Non linear and Dynamic Time Warping classification of morphological patterns identified from Plethysmographic observations in the radial pulse." In 2011 8th International Conference on Information, Communications & Signal Processing (ICICS 2011). IEEE, 2011. http://dx.doi.org/10.1109/icics.2011.6174292.

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Hatlinski, Grzegorz J., Witold Kornacki, Andrzej Kukwa, Bozena Dobrowiecka, and Marek Pikiel. "Application of digital signal processing methods for the diagnosis of respiration disorders during sleep with the use of plethysmographic wave analysis." In SPIE Proceedings, edited by Antoni Nowakowski and Bogdan B. Kosmowski. SPIE, 2004. http://dx.doi.org/10.1117/12.577618.

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