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Journal articles on the topic 'Photoplethysmography'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

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

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2

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

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3

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

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4

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

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5

Svistushkin, V. M., K. V. Eremeeva, X. Yang, et al. "Development of an experimental rabbit model of rhinitis medicamentosa." Russian Bulletin of Otorhinolaryngology 90, no. 3 (2025): 46. https://doi.org/10.17116/otorino20259003146.

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Background. Rhinitis medicamentosa (RM), resulting from prolonged use of nasal decongestants, represents a significant clinical problem. The pathogenetic mechanisms of RM remain insufficiently studied, and existing methods for assessing the state of the nasal mucosa require improvement. The development of an experimental model of RM is necessary for testing new therapeutic approaches. Objective. To develop an experimental model of RM in rabbits, evaluate morphological changes in the nasal mucosa, and test the photoplethysmography method for non-invasive diagnosis of microcirculatory disorders.

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6

Herrmann, Hans, and Hartmut Ewald. "Techniques of Recording Photoplethysmographic Signals." Current Directions in Biomedical Engineering 7, no. 2 (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 photopl

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7

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 r

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Cheshmedzhiev, Krasimir. "Analysis of Photopletismographic Signals at Different Sampling Rate." Innovative STEM Education 4, no. 1 (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 (2009): 975–85. http://dx.doi.org/10.1111/j.1399-6576.2009.02026.x.

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10

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

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11

Velyhotskyi, Dmytro, Serhii Duha, and Serhii Mamilov. "MULTIWAVELENGTH PHOTOPLETHYSMOGRAPHY SYSTEM." Bulletin of Kyiv Polytechnic Institute. Series Instrument Making, no. 69(1) (June 28, 2025): 106–18. https://doi.org/10.20535/1970.69(1).2025.331971.

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Photoplethysmography (PPG) is a promising technology for assessing the cardiovascular system's condition due to its ability to analyze changes in blood volume within the microvascular bed. Beyond standard parameters such as heart rate and blood oxygen saturation, the pulse wave shape in PPG signals contains additional valuable information that can be utilized for assessing heart rate variability, arterial stiffness, and blood pressure. However, the successful use of PPG in everyday activities requires reliable acquisition of signals free from saturation, motion artifacts, and other interferenc

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12

Desquins, Théo, Frédéric Bousefsaf, Alain Pruski, and Choubeila Maaoui. "A Survey of Photoplethysmography and Imaging Photoplethysmography Quality Assessment Methods." Applied Sciences 12, no. 19 (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 a

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13

Cheshmedzhiev, Krasimir. "Registering and Processing of a Photoplethysmography Signals." Innovative STEM Education 3, no. 1 (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

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14

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 il

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15

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 rec

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16

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 (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 c

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17

Feukeu, Etienne Alain, and Simon Winberg. "Photoplethysmography Heart Rate Monitoring." International Journal of E-Health and Medical Communications 12, no. 3 (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 segmen

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18

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

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19

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

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20

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 (1989): 257–69. http://dx.doi.org/10.1016/0169-2607(89)90159-4.

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21

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

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22

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

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23

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

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24

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

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25

Saikevičius, Linas, Vidas Raudonis, Agnė Kozlovskaja-Gumbrienė, and Gintarė Šakalytė. "Advancements in Remote Photoplethysmography." Electronics 14, no. 5 (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

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

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27

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 (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

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28

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 t

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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 (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 potenti

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30

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 (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, im

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31

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 fo

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Williamson, Simon, Lucie Daniel-Watanabe, Johanna Finnemann, et al. "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

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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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34

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 (2022): 355–81. http://dx.doi.org/10.1109/jproc.2022.3149785.

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35

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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36

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

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37

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

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38

Turcott, Robert G., and Todd J. Pavek. "Hemodynamic sensing using subcutaneous photoplethysmography." American Journal of Physiology-Heart and Circulatory Physiology 295, no. 6 (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 pr

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Allen, John, Klaus Overbeck, Gerard Stansby, and Alan Murray. "Photoplethysmography Assessments in Cardiovascular Disease." Measurement and Control 39, no. 3 (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 (2013): 087005. http://dx.doi.org/10.1117/1.jbo.18.8.087005.

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41

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

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42

Cheshmedzhiev, Krasimir. "A Photoplethysmography Signals Registering Device." Innovative STEM Education 2, no. 1 (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 (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

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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 (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

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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 (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 meth

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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 (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

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Killian, Jacquelin M., Rachel M. Radin, Cubby L. Gardner, et al. "Alternative Devices for Heart Rate Variability Measures: A Comparative Test–Retest Reliability Study." Behavioral Sciences 11, no. 5 (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 coeffic

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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 (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 sphygmog

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

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Abstract:

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 n

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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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Abstract:

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

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