Artykuły w czasopismach: „Photoplethysmography”

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Dorsey, J. Stonewall. "PHOTOPLETHYSMOGRAPHY." Plastic and Reconstructive Surgery 76, no. 5 (November 1985): 800. http://dx.doi.org/10.1097/00006534-198511000-00038.

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Alian, Aymen A., and Kirk H. Shelley. "Photoplethysmography." Best Practice & Research Clinical Anaesthesiology 28, no. 4 (December 2014): 395–406. http://dx.doi.org/10.1016/j.bpa.2014.08.006.

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Lindberg, L. G., T. Tamura, and P. Å. Öberg. "Photoplethysmography." Medical & Biological Engineering & Computing 29, no. 1 (January 1991): 40–47. http://dx.doi.org/10.1007/bf02446294.

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Lindberg, L. G., and P. Å. Öberg. "Photoplethysmography." Medical & Biological Engineering & Computing 29, no. 1 (January 1991): 48–54. http://dx.doi.org/10.1007/bf02446295.

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Herrmann, Hans, and Hartmut Ewald. "Techniques of Recording Photoplethysmographic Signals." Current Directions in Biomedical Engineering 7, no. 2 (October 1, 2021): 143–46. http://dx.doi.org/10.1515/cdbme-2021-2037.

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Abstract The photoplethysmography optically measures blood volume changes within micro vascular tissue. Furthermore, photoplethysmographic signals are used within pulse oximeters in order to calculate the oxygen saturation of the blood. This standard measurement technique is performed as a non-invasive spot check method for human health conditions in hospitals or other health care facilities. Usually at least two light sources are used alternating in order to measure photoplethysmograms at different wavelengths. In this paper we will investigate different methods of optically recording photoplethysmographic signals.

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Peng, Rong-Chao, Wen-Rong Yan, Ning-Ling Zhang, Wan-Hua Lin, Xiao-Lin Zhou, and Yuan-Ting Zhang. "Investigation of Five Algorithms for Selection of the Optimal Region of Interest in Smartphone Photoplethysmography." Journal of Sensors 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/6830152.

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Smartphone photoplethysmography is a newly developed technique that can detect several physiological parameters from the photoplethysmographic signal obtained by the built-in camera of a smartphone. It is simple, low-cost, and easy-to-use, with a great potential to be used in remote medicine and home healthcare service. However, the determination of the optimal region of interest (ROI), which is an important issue for extracting photoplethysmographic signals from the camera video, has not been well studied. We herein proposed five algorithms for ROI selection: variance (VAR), spectral energy ratio (SER), template matching (TM), temporal difference (TD), and gradient (GRAD). Their performances were evaluated by a 50-subject experiment comparing the heart rates measured from the electrocardiogram and those from the smartphone using the five algorithms. The results revealed that the TM and the TD algorithms outperformed the other three as they had less standard error of estimate (<1.5 bpm) and smaller limits of agreement (<3 bpm). The TD algorithm was slightly better than the TM algorithm and more suitable for smartphone applications. These results may be helpful to improve the accuracy of the physiological parameters measurement and to make the smartphone photoplethysmography technique more practical.

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Cheshmedzhiev, Krasimir. "Analysis of Photopletismographic Signals at Different Sampling Rate." Innovative STEM Education 4, no. 1 (June 10, 2022): 56–61. http://dx.doi.org/10.55630/stem.2022.0408.

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Photoplethysmography is a convenient and easy to use method for obtaining information about the human cardiovascular system. It is based on the use of the property of tissues to absorb light passing through or reflected from them. The received analog signal when using this method is converted into digital for further processing. The article presents an experimental system for recording photoplethysmographic signals. The data obtained during the digitization of the analog signal with different sampling rates are shown.

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KORHONEN, I., and A. YLI-HANKALA. "Photoplethysmography and nociception." Acta Anaesthesiologica Scandinavica 53, no. 8 (September 2009): 975–85. http://dx.doi.org/10.1111/j.1399-6576.2009.02026.x.

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Gailite, L., J. Spigulis, and A. Lihachev. "Multilaser photoplethysmography technique." Lasers in Medical Science 23, no. 2 (July 14, 2007): 189–93. http://dx.doi.org/10.1007/s10103-007-0471-9.

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Desquins, Théo, Frédéric Bousefsaf, Alain Pruski, and Choubeila Maaoui. "A Survey of Photoplethysmography and Imaging Photoplethysmography Quality Assessment Methods." Applied Sciences 12, no. 19 (September 23, 2022): 9582. http://dx.doi.org/10.3390/app12199582.

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Photoplethysmography is a method to visualize the variation in blood volume within tissues with light. The signal obtained has been used for the monitoring of patients, interpretation for diagnosis or for extracting other physiological variables (e.g., pulse rate and blood oxygen saturation). However, the photoplethysmography signal can be perturbed by external and physiological factors. Implementing methods to evaluate the quality of the signal allows one to avoid misinterpretation while maintaining the performance of its applications. This paper provides an overview on signal quality index algorithms applied to photoplethysmography. We try to provide a clear view on the role of a quality index and its design. Then, we discuss the challenges arising in the quality assessment of imaging photoplethysmography.

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Cheshmedzhiev, Krasimir. "Registering and Processing of a Photoplethysmography Signals." Innovative STEM Education 3, no. 1 (June 29, 2021): 13–19. http://dx.doi.org/10.55630/stem.2021.0302.

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Heart rate variability (HRV) is a non-invasive indicator of the condition of the cardiovascular system. To calculate HRV, the time between two adjacent R peaks of the electrocardiogram of the individual is used, i.e. between two heartbeats. This method requires the placement of electrodes in certain places on the body of the individual. An alternative way to measure heart rate is to use the change in blood volume in the blood vessels, through optical method, so-called photoplethysmography. It is based on the measurement of the change in light absorption depending on the amount of blood in the blood vessels. This article discusses ways to capture photoplethysmographic signals and convert them into data suitable for further processing. Graphs of the data from experimental studies at different stages of their processing are presented.

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Ju, Bin, Yun Tao Qian, and Huo Jie Ye. "Wavelet Based Measurement on Photoplethysmography by Smartphone Imaging." Applied Mechanics and Materials 380-384 (August 2013): 773–77. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.773.

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[Purpose] Smartphones video cameras can be used to detect the photoplethysmograph (PPG) signal.The pulse wave signal detected by smartphone always mixed mass noise because of finger moving, unevenness of pressure and outer light interference. Previous studies limit to the filtering algorithm that denoising signals, without considering characteristics information of pulse wave itself. [Method] In this paper, we propose an algorithm based on wavelet to detect qualified PPG, which captures three critical characteristic quantities through wavelet high frequency coefficient. [Results] Experiment illustrates that the detected PPG signal contain dicrotic wave, and whats more, further experiment on artery elasticity indexes indicates good robust of the algorithm. [Conclusions] Wavelet Based Measurement on Photoplethysmography by Smartphone Imaging can be used for the calculation of cardiovascular parameter such as angiosclerosis, arrhythmia, and vascular resistance.

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Antonsen, Lars Prag, and Knut Arvid Kirkebøen. "Evaluation of Fluid Responsiveness: Is Photoplethysmography a Noninvasive Alternative?" Anesthesiology Research and Practice 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/617380.

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Background. Goal-directed fluid therapy reduces morbidity and mortality in various clinical settings. Respiratory variations in photoplethysmography are proposed as a noninvasive alternative to predict fluid responsiveness during mechanical ventilation. This paper aims to critically evaluate current data on the ability of photoplethysmography to predict fluid responsiveness.Method. Primary searches were performed in PubMed, Medline, and Embase on November 10, 2011.Results. 14 papers evaluating photoplethysmography and fluid responsiveness were found. Nine studies calculated areas under the receiver operating characteristic curves forΔPOP (>0.85 in four, 0.75–0.85 in one, and <0.75 in four studies) and seven for PVI (values ranging from 0.54 to 0.98). Correlations betweenΔPOP/PVI andΔPP/other dynamic variables vary substantially.Conclusion. Although photoplethysmography is a promising technique, predictive values and correlations with other hemodynamic variables indicating fluid responsiveness vary substantially. Presently, it is not documented that photoplethysmography is adequately valid and reliable to be included in clinical practice for evaluation of fluid responsiveness.

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Yen, Chih-Ta, Sheng-Nan Chang, and Cheng-Hong Liao. "Deep learning algorithm evaluation of hypertension classification in less photoplethysmography signals conditions." Measurement and Control 54, no. 3-4 (March 2021): 439–45. http://dx.doi.org/10.1177/00202940211001904.

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This study used photoplethysmography signals to classify hypertensive into no hypertension, prehypertension, stage I hypertension, and stage II hypertension. There are four deep learning models are compared in the study. The difficulties in the study are how to find the optimal parameters such as kernel, kernel size, and layers in less photoplethysmographyt (PPG) training data condition. PPG signals were used to train deep residual network convolutional neural network (ResNetCNN) and bidirectional long short-term memory (BILSTM) to determine the optimal operating parameters when each dataset consisted of 2100 data points. During the experiment, the proportion of training and testing datasets was 8:2. The model demonstrated an optimal classification accuracy of 76% when the testing dataset was used.

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Feukeu, Etienne Alain, and Simon Winberg. "Photoplethysmography Heart Rate Monitoring." International Journal of E-Health and Medical Communications 12, no. 3 (May 2021): 17–37. http://dx.doi.org/10.4018/ijehmc.20210501.oa2.

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Research conducted by the World Health Organisation (WHO) in 2018 demonstrated that the worldwide threat of cardiovascular diseases (CVDs) has increased compared to previous years. CVDs are very dangerous: if timely treatment is not performed, these conditions could become irreversible and lead to sudden death. Prescriptive measures include physical exercises and monitoring of the heart rate (HR). Despite the existence of various HR monitoring devices (or HMDs), a major challenge remains their availability, particularly to people in lower-income countries. Unfortunately, it is also this segment of the population that is the most vulnerable to CVDs. Accordingly, this led the authors to propose the design for an easily constructible state-of-the-art HMD that attempts to provide a highly accessible, lower-cost, and long-lasting solution that would be more affordable and accessible to these low-income communities.

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Hayes, Matthew J., and Peter R. Smith. "Artifact reduction in photoplethysmography." Applied Optics 37, no. 31 (November 1, 1998): 7437. http://dx.doi.org/10.1364/ao.37.007437.

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Komatsu, Kan-ichiro, Toshio Fukutake, and Takamichi Hattori. "Fingertip photoplethysmography and migraine." Journal of the Neurological Sciences 216, no. 1 (December 2003): 17–21. http://dx.doi.org/10.1016/s0022-510x(03)00208-9.

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Kamal, A. A. R., J. B. Harness, G. Irving, and A. J. Mearns. "Skin photoplethysmography — a review." Computer Methods and Programs in Biomedicine 28, no. 4 (April 1989): 257–69. http://dx.doi.org/10.1016/0169-2607(89)90159-4.

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Nilsson, Lena M. "Respiration Signals from Photoplethysmography." Anesthesia & Analgesia 117, no. 4 (October 2013): 859–65. http://dx.doi.org/10.1213/ane.0b013e31828098b2.

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BOURDILLON, NICOLAS, MASIH NILCHIAN, and GRÉGOIRE P. MILLET. "Photoplethysmography Detection of Overreaching." Medicine & Science in Sports & Exercise 51, no. 4 (April 2019): 701–7. http://dx.doi.org/10.1249/mss.0000000000001836.

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Burke, M. J., and M. V. Whelan. "Photoplethysmography: Selecting optoelectronic components." Medical & Biological Engineering & Computing 24, no. 6 (November 1986): 647–50. http://dx.doi.org/10.1007/bf02446270.

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Sahni, Rakesh. "Noninvasive Monitoring by Photoplethysmography." Clinics in Perinatology 39, no. 3 (September 2012): 573–83. http://dx.doi.org/10.1016/j.clp.2012.06.012.

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Saikevičius, Linas, Vidas Raudonis, Agnė Kozlovskaja-Gumbrienė, and Gintarė Šakalytė. "Advancements in Remote Photoplethysmography." Electronics 14, no. 5 (March 3, 2025): 1015. https://doi.org/10.3390/electronics14051015.

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Advancements in camera technology over the past two decades have made image-based monitoring increasingly accessible for healthcare applications. Imaging photoplethysmography (iPPG) and remote photoplethysmography (rPPG) are non-invasive methods for measuring vital signs, such as heart rate, respiratory rate, oxygen saturation, and blood pressure, without physical contact. rPPG utilizes basic cameras to detect physiological changes, while rPPG enables remote monitoring by capturing subtle skin colour variations linked to blood flow. Various rPPG techniques, including colour-based, motion-based, multispectral, and depth-based approaches, enhance accuracy and resilience. These technologies are beneficial not only for healthcare but also for fitness tracking, stress management, and security systems, offering a promising future for contactless physiological monitoring. In this article, there is an overview of these methods and their uniqueness for use in remote photoplethysmography.

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Saikevičius, Linas, Vidas Raudonis, Agnė Kozlovskaja-Gumbrienė, and Gintarė Šakalytė. "Advancements in Remote Photoplethysmography." Electronics 14, no. 5 (March 3, 2025): 1015. https://doi.org/10.3390/electronics14051015.

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Sharif-Kashani, Babak, Neda Behzadnia, Payman Shahabi, and Makan Sadr. "Screening for Deep Vein Thrombosis in Asymptomatic High-risk Patients: A Comparison between Digital Photoplethysmography and Venous Ultrasonography." Angiology 60, no. 3 (October 14, 2008): 301–7. http://dx.doi.org/10.1177/0003319708323494.

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Objective To determine the role of digital photoplethysmography in screening asymptomatic patients who are susceptible for developing deep vein thrombosis. Methods Three hundred and thirty-seven limbs in 169 patients who were high risk for development of deep vein thrombosis were assessed by ultrasonography digital photoplethysmography and the results were compared. Results Thirteen limbs were found to have deep vein thrombosis as demonstrated by ultrasonography. All limbs with a venous refilling time greater than 12 seconds had a normal ultrasonography. Compared with ultrasonography and using refilling time less than 12 seconds as the cutoff point, digital photoplethysmography achieved a sensitivity, specificity, positive predictive value, and negative predictive value of 100%, 73.8%, 13.3%, and 100% respectively, for detecting deep vein thrombosis in asymptomatic high-risk patients. Conclusion Digital photoplethysmography is a simple, noninvasive, and highly sensitive test for screening of deep vein thrombosis.

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Jeong, Jae Hoon, Sung Min Kim, Sung Yun Park, and Sangjoon Lee. "A Study on Measurement of Photoplethysmograph Using a Smartphone Camera." Applied Mechanics and Materials 479-480 (December 2013): 137–42. http://dx.doi.org/10.4028/www.scientific.net/amm.479-480.137.

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In this study, we proposed a method for measuring photoplethysmographic using a smartphone camera. A development algorithm is consists 6 procedures. The first is to convert RGB to Gray level from a camera image, the second is to detect ROI from image, the third is to extract photoplethysmography signal from a camera image, the fourth is to filter baseline, and the last is to oversample procedure using cubic spline interpolation. The proposed algorithm has been tested using several smartphone with a person and which can effectively acquire persons PPG signal at any situation. We supposed that the proposed algorithm can easily adapt for a smartphone m-health system.

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Diana, Gianluca, Francesco Scardulla, Silvia Puleo, Salvatore Pasta, and Leonardo D’Acquisto. "Non-Invasive Estimation of Arterial Stiffness Using Photoplethysmography Sensors: An In Vitro Approach." Sensors 25, no. 11 (May 24, 2025): 3301. https://doi.org/10.3390/s25113301.

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With advancing age, blood vessels undergo deterioration that causes structural and functional changes, including a progressive increase in arterial wall stiffness. Since arterial stiffness is closely linked to the potential risks of cardiovascular diseases, which remains the leading cause of global mortality, it has become essential to develop effective techniques for early diagnosis and continuous monitoring over time. Photoplethysmography, a low-cost and non-invasive technology that measures blood volume changes, has gained increasing popularity in recent years and has proven to be a potential valuable tool for estimating arterial stiffness. This study employs an in vitro experimental setup designed to simulate the cardiovascular system performing under controlled velocity and pressure conditions, in which silicone phantom models with different geometric and mechanical properties were implemented to evaluate their stiffness using a pair of photoplethysmographic sensors. These were employed to measure the pulse wave velocity, currently considered the reference technique for estimating arterial stiffness, correlated through the well-known Moens–Korteweg equation. Photoplethysmographic sensors were placed at three specific distances to determine an optimal configuration for assessing arterial stiffness. Results showed the best performance for softer vascular models at a 15 cm sensor distance, with measurements demonstrating satisfactory accuracy. Variability and standard deviation values increased with model stiffness. The aim of this study is to improve the use of photoplethysmographic sensors for monitoring the mechanical properties of blood vessels and, therefore, to prevent potential cardiovascular diseases.

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Berezhnyi, Ihor, and Adrian Nakonechnyi. "Analysis of Methods and Algorithms for Remote Photoplethysmography Signal Diagnostic and Filtering." Advances in Cyber-Physical Systems 9, no. 1 (May 10, 2024): 82–88. http://dx.doi.org/10.23939/acps2024.01.082.

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Remote photoplethysmography is becoming increasingly common in telemedicine for non-invasive physiological monitoring of the cardiovascular system. However, signal reliability has been reduced due to noise and artifacts, which requires reliable diagnostic and filtering methods. The research aim is to evaluate existing methods and algorithms for diagnosing and filtering remote photoplethysmography signals to improve the accuracy of human cardiovascular monitoring. A systematic review has identified methodologies for improving remote photoplethysmography signals by analyzing their principles, implementation, and effectiveness. Various approaches have been analyzed, including the use of statistical computing, adaptive filters, and machine learning algorithms. Each approach offers unique advantages and limitations in terms of noise reduction and artifact removal.

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Wong, Mark Kei Fong, Hao Hei, Si Zhou Lim, and Eddie Yin-Kwee Ng. "Applied machine learning for blood pressure estimation using a small, real-world electrocardiogram and photoplethysmogram dataset." Mathematical Biosciences and Engineering 20, no. 1 (2022): 975–97. http://dx.doi.org/10.3934/mbe.2023045.

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<abstract> <p>Applying machine learning techniques to electrocardiography and photoplethysmography signals and their multivariate-derived waveforms is an ongoing effort to estimate non-occlusive blood pressure. Unfortunately, real ambulatory electrocardiography and photoplethysmography waveforms are inevitably affected by motion and noise artifacts, so established machine learning architectures perform poorly when trained on data of the Multiparameter Intelligent Monitoring in Intensive Care II type, a publicly available ICU database. Our study addresses this problem by applying four well-established machine learning methods, i.e., random forest regression, support vector regression, Adaboost regression and artificial neural networks, to a small, self-sampled electrocardiography-photoplethysmography dataset (n = 54) to improve the robustness of machine learning to real-world BP estimates. We evaluated the performance using a selection of optimal feature morphologies of waveforms by using pulse arrival time, morphological and frequency photoplethysmography parameters and heart rate variability as characterization data. On the basis of the root mean square error and mean absolute error, our study showed that support vector regression gave the best performance for blood pressure estimation from noisy data, achieving an mean absolute error of 6.97 mmHg, which meets the level C criteria set by the British Hypertension Society. We demonstrate that ambulatory electrocardiography- photoplethysmography signals acquired by mobile discrete devices can be used to estimate blood pressure.</p> </abstract>

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Williamson, Simon, Lucie Daniel-Watanabe, Johanna Finnemann, Craig Powell, Adam Teed, Micah Allen, Martin Paulus, Sahib S. Khalsa, and Paul C. Fletcher. "The Hybrid Excess and Decay (HED) model: an automated approach to characterising changes in the photoplethysmography pulse waveform." Wellcome Open Research 7 (August 17, 2022): 214. http://dx.doi.org/10.12688/wellcomeopenres.17855.1.

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Photoplethysmography offers a widely used, convenient and non-invasive approach to monitoring basic indices of cardiovascular function, such as heart rate and blood oxygenation. Systematic analysis of the shape of the waveform generated by photoplethysmography might be useful to extract estimates of several physiological and psychological factors influencing the waveform. Here, we developed a robust and automated method for such a systematic analysis across individuals and across different physiological and psychological contexts. We describe a psychophysiologically-relevant model, the Hybrid Excess and Decay (HED) model, which characterises pulse wave morphology in terms of three underlying pressure waves and a decay function. We present the theoretical and practical basis for the model and demonstrate its performance when applied to a pharmacological dataset of 105 participants receiving intravenous administrations of the sympathomimetic drug isoproterenol (isoprenaline). We show that these parameters capture photoplethysmography data with a high degree of precision and, moreover, are sensitive to experimentally-induced changes in interoceptive arousal within individuals. We conclude by discussing the possible value in using the HED model as a complement to standard measures of photoplethysmography signals.

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Deshpande, Alaka, Sadhana A. Mandlik, Aparna S. Lakhe, Jyoti V. Jethe, and Vinnet Sinha. "Photoplethysmography and Its Clinical Application." MGM Journal of Medical Sciences 4, no. 2 (2017): 89–96. http://dx.doi.org/10.5005/jp-journals-10036-1146.

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Charlton, Peter H., Panicos A. Kyriacou, Jonathan Mant, Vaidotas Marozas, Phil Chowienczyk, and Jordi Alastruey. "Wearable Photoplethysmography for Cardiovascular Monitoring." Proceedings of the IEEE 110, no. 3 (March 2022): 355–81. http://dx.doi.org/10.1109/jproc.2022.3149785.

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Maeda, Yuka, Masaki Sekine, Toshiyo Tamura, Takuji Suzuki, and Ken-ichi Kameyama. "Performance evaluation of green photoplethysmography." Journal of Life Support Engineering 19, Supplement (2007): 183. http://dx.doi.org/10.5136/lifesupport.19.supplement_183.

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Kozioł, Maciej, Piotr Piech, Marcin Maciejewski, and Wojciech Surtel. "The latest applications of photoplethysmography." Acta Angiologica 25, no. 1 (March 20, 2019): 28–34. http://dx.doi.org/10.5603/aa.2019.0005.

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Holton, Benjamin D., Kavan Mannapperuma, Peter J. Lesniewski, and John C. Thomas. "Signal recovery in imaging photoplethysmography." Physiological Measurement 34, no. 11 (October 22, 2013): 1499–511. http://dx.doi.org/10.1088/0967-3334/34/11/1499.

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Turcott, Robert G., and Todd J. Pavek. "Hemodynamic sensing using subcutaneous photoplethysmography." American Journal of Physiology-Heart and Circulatory Physiology 295, no. 6 (December 2008): H2560—H2572. http://dx.doi.org/10.1152/ajpheart.00574.2008.

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Pacemakers and implantable defibrillators presently operate without access to hemodynamic information. If available, such data would allow tailoring of delivered therapy according to perfusion status, optimization of device function, and enhancement of disease monitoring and management. A candidate method for hemodynamic sensing in these devices is photoplethysmography (PPG), which uses light to noninvasively detect changes in blood volume. The present study tested the hypotheses that PPG can function in a subcutaneous location, that the acute changes in blood volume it detects are directly proportional to changes in arterial pressure, and that optimum pacing intervals identified by it are concordant with those determined by arterial pressure. Aortic pressure and PPG were simultaneously recorded in 10 dogs under general anesthesia during changes in atrioventricular (AV) delay and bursts of rapid pacing to simulate tachyarrhythmias. Direct proportionality between transient changes in pressure and PPG waveforms was tested using regression analysis. Scatter plots had a linear appearance, with correlation coefficients of 0.95 (SD 0.03) and 0.72 (SD 0.24) for rapid-pacing and AV delay protocols, respectively. The data were well described by a directly proportional relationship. Optimum AV delays estimated from the induced changes in aortic pressure and PPG waveforms were concordant. This preliminary canine study demonstrates that PPG can function subcutaneously and that it may serve as a surrogate for acute changes in arterial pressure.

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Allen, John, Klaus Overbeck, Gerard Stansby, and Alan Murray. "Photoplethysmography Assessments in Cardiovascular Disease." Measurement and Control 39, no. 3 (April 2006): 80–83. http://dx.doi.org/10.1177/002029400603900303.

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Akl, Tony J., Mark A. Wilson, M. Nance Ericson, and Gerard L. Coté. "Intestinal perfusion monitoring using photoplethysmography." Journal of Biomedical Optics 18, no. 8 (August 12, 2013): 087005. http://dx.doi.org/10.1117/1.jbo.18.8.087005.

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Turcott, Robert G., and Todd J. Pavek. "Pacing interval optimization using photoplethysmography." Journal of Cardiac Failure 10, no. 4 (August 2004): S73. http://dx.doi.org/10.1016/j.cardfail.2004.06.203.

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Cheshmedzhiev, Krasimir. "A Photoplethysmography Signals Registering Device." Innovative STEM Education 2, no. 1 (August 10, 2020): 13–20. http://dx.doi.org/10.55630/stem.2020.0202.

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Monitoring a heart rate provides an essential information about health status of a subjects. Photoplethysmography is a low-cost optical technique to monitor blood volume changes in human body. In this article is presented a portable microcontroller system to register PPG signals from two types of sensors, convert them and store data on internal storage or send it to personal computer for next processing.

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Garanin, А. А., V. S. Rogova, P. S. Ivanchina, and E. O. Tolkacheva. "Web photoplethysmography: opportunities and prospects." Regional blood circulation and microcirculation 22, no. 4 (December 27, 2023): 11–16. http://dx.doi.org/10.24884/1682-6655-2023-22-4-11-16.

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This literature review is devoted to the possibilities of using in clinical practice a new modification of photoplethysmography – its web version. The use of modern innovative techniques in the form of photo/video fixation of the human skin allows for contactless and remote assessment of the main physiological indicators of human health. This approach is of particular importance in conditions of shortage of medical workers, territorial separation of doctors and patients, restrictions in visiting medical institutions in the event of epidemics/pandemics of infectious diseases and it contributes to the development and implementation of telemedicine technologies in the daily work of medical specialists. The article discusses the possibilities of using web photoplethysmography to assess microcirculation (web capillaroscopy), heart rate and other indicators (respiratory rate, pulse rate, saturation, body temperature, etc.). Web photoplethysmography is a sensitive, simple and effective method of registering vital body functions. Its effectiveness as a possible screening method for detecting rhythm disturbances and its prospects in using blood pressure measurement has already been proven. The possibility of using not only video, but also photographic materials, for example, for the detection of cardiovascular diseases, is also described. No less promising is the possibility of using the method in conjunction with thermometry. The importance of studying aspects of web photoplethysmography is seen in the need to activate the processes of import substitution and technological sovereignty, as one of the main paradigms of our country’s development. It is obvious that the development of contactless research methods is one of the priorities in modern healthcare. Given the widespread availability of various devices, it is necessary to further explore the possibilities of using webcams and mobile devices in medical practice. The development and introduction into routine practice of medical devices that allow remote non-invasive early diagnosis of chronic non-communicable diseases is of special interest.

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Nikitchuk, Tetiana M., Tetiana A. Vakaliuk, Oksana A. Chernysh, Oksana L. Korenivska, Liudmyla A. Martseva, and Viacheslav V. Osadchyi. "Non-contact photoplethysmographic sensors for monitoring students' cardiovascular system functional state in an IoT system." Journal of Edge Computing 1, no. 1 (November 21, 2022): 17–28. http://dx.doi.org/10.55056/jec.570.

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This article explores the technical feasibility of a hardware complex that employs photoplethysmographic sensors to measure the parameters of students' cardiovascular system functional state. The method of photoplethysmography utilizes non-contact sensors, which eliminate circulatory disorders caused by artery compression and enable the calculation of oxygen saturation via the pulse wave. The proposed hardware consists of several optocouplers arranged in series, parallel, or parallel-series configurations, with the mode of operation controlled by the intensity of the received pulse wave signal, depending on the individual's body constitution. The edge device hardware is a component of an Internet of Things (IoT) system that includes another edge device, which instantaneously transmits data to a database on the edge server for further processing and storage.

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Kim, Seung-Hyun, Su-Min Jeon, and Eui Chul Lee. "Face Biometric Spoof Detection Method Using a Remote Photoplethysmography Signal." Sensors 22, no. 8 (April 16, 2022): 3070. http://dx.doi.org/10.3390/s22083070.

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Spoofing attacks in face recognition systems are easy because faces are always exposed. Various remote photoplethysmography-based methods to detect face spoofing have been developed. However, they are vulnerable to replay attacks. In this study, we propose a remote photoplethysmography-based face recognition spoofing detection method that minimizes the susceptibility to certain database dependencies and high-quality replay attacks without additional devices. The proposed method has the following advantages. First, because only an RGB camera is used to detect spoofing attacks, the proposed method is highly usable in various mobile environments. Second, solutions are incorporated in the method to obviate new attack scenarios that have not been previously dealt with. In this study, we propose a remote photoplethysmography-based face recognition spoofing detection method that improves susceptibility to certain database dependencies and high-quality replay attack, which are the limitations of previous methods without additional devices. In the experiment, we also verified the cut-off attack scenario in the jaw and cheek area where the proposed method can be counter-attacked. By using the time series feature and the frequency feature of the remote photoplethysmography signal, it was confirmed that the accuracy of spoof detection was 99.7424%.

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Snizhko, Y. M., O. O. Boiko, N. P. Botsva, D. V. Chernetchenko, and M. M. Milyh. "Methods for increasing the accuracy of recording the parameters of the cardiovascular system in double-beam photoplethysmography." Regulatory Mechanisms in Biosystems 9, no. 3 (July 24, 2018): 335–39. http://dx.doi.org/10.15421/021849.

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Photoplethysmography has recently become more widespread among non-invasive methods for obtaining information on the state of physiological systems of the human body. Serial photoplethysmographs are intended for use in clinics and require special care, therefore, interest in portable media developed on the basis of modern sensors and microcontrollers is growing, which would not only make this method available for individual use, but also expand its capabilities through the use of light of various spectral ranges. Such devices require modified signal processing techniques that allow them to be used in mobile applications. The aim of the work is to develop methods for processing signals from a modern two-beam sensor operating in the red and infrared ranges for the analysis of photoplethysmography on a mobile device (smartphone or tablet). A device using the microcontroller and radio module in the Bluetooth standard allows you to continuously record pulse waves, determine the level of oxygen in the blood, calculate peak-peak intervals and heart rate. The use of the two-beam sensor for registration and the implementation of the developed signal processing methods in the Android operation system application increase the accuracy of setting the maximums on pulse curve and provide a relative error in determining the heart rate and pulse-to-pulse intervals relative to the certified electrocardiograph at 9.2% and 9.6% respectively, with an average level of interference and an average activity. An Android operation system mobile device (tablet, smartphone) allows you to visualize the measurement results, store data in the internal memory, and transfer them to the server for further processing.

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Killian, Jacquelin M., Rachel M. Radin, Cubby L. Gardner, Lalon Kasuske, Kylee Bashirelahi, Dominic Nathan, David O. Keyser, Christopher J. Cellucci, David Darmon, and Paul E. Rapp. "Alternative Devices for Heart Rate Variability Measures: A Comparative Test–Retest Reliability Study." Behavioral Sciences 11, no. 5 (May 2, 2021): 68. http://dx.doi.org/10.3390/bs11050068.

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Using healthy adult participants, seven measures of heart rate variability were obtained simultaneously from four devices in five behavioral conditions. Two devices were ECG-based and two utilized photoplethysmography. The 140 numerical values (measure, condition, device) are presented. The comparative operational reliability of the four devices was assessed, and it was found that the two ECG-base devices were more reliable than the photoplethysmographic devices. The interchangeability of devices was assessed by determining the between-device Limits of Agreement. Intraclass correlation coefficients were determined and used to calculate the standard error of measurement and the Minimal Detectable Difference. The Minimal Detectable Difference, MDD, quantifies the smallest statistically significant change in a measure and is therefore critical when HRV measures are used longitudinally to assess treatment response or disease progression.

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O’Neill, Christopher. "Haptic media and the cultural techniques of touch: The sphygmograph, photoplethysmography and the Apple Watch." New Media & Society 19, no. 10 (July 18, 2017): 1615–31. http://dx.doi.org/10.1177/1461444817717514.

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This article draws upon cultural techniques theory to propose an approach to studying haptic media as media technologies which train or discipline touch and which serve to produce touch itself as a coherent and ‘proper’ communicative technology. This article analyses the different forms of touch which have coalesced around the sphygmograph, a nineteenth-century pulse writing technology, and photoplethysmography, a contemporary heart rate–measuring technology which has been remediated as part of the Apple Watch. This article demonstrates that nineteenth-century clinicians drew upon the sphygmograph to authorise doctorly touch as newly ‘proper’ within a changed technological context. By contrast, an analysis of the place of error within the Apple Watch’s photoplethysmograph demonstrates how contemporary self-quantifiers are encumbered with an unreliable measuring apparatus which can only generalise a form of ‘improper’ touch, touch which fails to know the body and which remains tied to a ‘proper’ touch which lies elsewhere.

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Romadhoni, Titoriski, Endang Dian Setioningsih, and M. Prastawa Assalim T. Putra. "Photoplethysmograph Portable." Jurnal Teknokes 12, no. 1 (September 19, 2019): 21–26. http://dx.doi.org/10.35882/teknokes.v12i1.4.

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Photoplethysmograph (PPG) merupakan metode yang digunakan untuk mengetahui kondisi sistem kardiovaskular dengan mengukur perubahan volume darah pada jaringan kulit. Dalam penerapannya, metode ini menggunakan sensor optik untuk menangkap sinyal elektrik yang berasal dari sumber cahaya yang lewat atau dipantulkan. Penelitian terakhir monitoring photoplethysmography yang memiliki kemampuan mengirim melalui Bluetooth HC-05 tetapi penelitian tersebut terpisah antara alat dan display sehingga kurang praktis. Maka dari itu dibuatlah perancangan ini, yang dapat menampilkan sinyal PPG disertai dengan nilai SpO2 (saturasi oksigen kapiler perifer) dan BPM (Beat per Minutes) ditampilkan pada LCD TFT agar dapat mempermudah dalam memonitoring sinyal PPG tersebut.Pengujian alat ini dilakukan dengan membandingkan modul dengan alat ukur oximeter yang menghasilkan rata-rata %error pengukuran SpO2 sebesar 0,486 % dengan toleransi maksimum yang diizinkan ± 1%, sedangkan pada parameter BPM didapatkan rata-rata %error sebesar 0,683 % dengan toleransi maksimum yang diizinkan ± 5%.

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Gerzhik, A. A., and I. A. Raznitsyna. "Experimental Substantiation of a Number of Requirements for Hardware and Methodology of Non-Contact Photoplethysmography Based on Video Image Analysis." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 4 (137) (December 2021): 122–38. http://dx.doi.org/10.18698/0236-3933-2021-4-122-138.

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Experimental assessment of the possibility of using a scientific video camera for realization of non-contact photoplethysmography is carried out. In view of the wide spread of digital cameras in endoscopic units photoplethysmography based on video-image analysis is an inexpensive and promising method for solving problems of medical diagnostics. A number of requirements to the camera parameters ensuring the specified level of the registered signals coded by RGB values, to the external illumination and video image postprocessing algorithms was substantiated. It was found that at signal levels on the green channel of not less than 130 and not more than 220 a. u. (for a camera with 8-bit color coding depth), the highest level of useful pulse signal is provided. It was shown that any source of light of equivalent color temperature in the range of 3500--6500 K as well as green LEDs can be used as a light source to obtain a high-quality signal of non-contact photoplethysmography. It is demonstrated that the signal has higher signal/noise ratio when the averaging area is larger than 40 × 40 pixels than when averaging over a smaller group of pixels. The obtained results can be used for the implementation of non-contact photoplethysmography to study local blood flow based on video image analysis

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Gircys, Rolandas, Agnius Liutkevicius, Arunas Vrubliauskas, and Egidijus Kazanavicius. "Blood Pressure Estimation Accoording to Photoplethysmographic Signal Steepness." Information Technology And Control 44, no. 4 (December 18, 2015): 443–50. http://dx.doi.org/10.5755/j01.itc.44.4.12562.

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Abstract. The purpose of this paper is to prove the assumption that there is a correlation between the systolic blood pressure and the photoplethysmographic signal steepness. A method for indirect systolic blood pressure estimation based on photoplethysmographic signal steepness is proposed in this paper. Method: It is proved that based on Hooke’s law, the steepness of pressure and volume (diameter) of pulse waves differ by a constant. The coefficient for calculating arterial blood pressure when volume pulse wave steepness is known is presented in this paper. The Windkessel model is selected for the modeling. Experimental evaluation is based on veloergometrical trials. Volume pulse wave was obtained using a photoplethysmography device that is put on a finger. Blood pressure was measured using a semi-automatic OMRON blood pressure monitor. Results: The simulation of an arterial system using the Windkessel model shows that the steepness of pressure and volume pulse waves correlate. Ten veloergometrical trials were performed during the experimental evaluation. A significant 0.855±0.025 (p < 0.001) correlation between the photoplethysmographic signal steepness and the systolic blood pressure was obtained. The calculated and measured blood pressure values vary no more than ±5mmHg. Conclusions: The results demonstrate that the photoplethysmographic signal wavefront can be successfully applied in wearable devices that can be used for constant 24 hour registration of blood pressure for both home use and clinical practice.DOI: http://dx.doi.org/10.5755/j01.itc.44.4.12562

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Zangróniz, Roberto, Arturo Martínez-Rodrigo, María López, José Pastor, and Antonio Fernández-Caballero. "Estimation of Mental Distress from Photoplethysmography." Applied Sciences 8, no. 1 (January 5, 2018): 69. http://dx.doi.org/10.3390/app8010069.

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