The DOI matches its Crossref record; 277 of the 277 references it cites were found in a registry or an index.
Photoplethysmography and its application in clinical physiological measurement
Open accessAbstract
Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile ('AC') physiological waveform attributed to cardiac synchronous changes in the blood volume with each heart beat, and is superimposed on a slowly varying ('DC') baseline with various lower frequency components attributed to respiration, sympathetic nervous system activity and thermoregulation. Although the origins of the components of the PPG signal are not fully understood, it is generally accepted that they can provide valuable information about the cardiovascular system. There has been a resurgence of interest in the technique in recent years, driven by the demand for low cost, simple and portable technology for the primary care and community based clinical settings, the wide availability of low cost and small semiconductor components, and the advancement of computer-based pulse wave analysis techniques. The PPG technology has been used in a wide range of commercially available medical devices for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and also detecting peripheral vascular disease. The introductory sections of the topical review describe the basic principle of operation and interaction of light with tissue, early and recent history of PPG, instrumentation, measurement protocol, and pulse wave analysis. The review then focuses on the applications of PPG in clinical physiological measurements, including clinical physiological monitoring, vascular assessment and autonomic function.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Prior research has suggested that PPG sensors used to measure the HR are liable to poor accuracy during activities with increased physical exertion or activities involving repetitive contractions of forearm skeletal muscles [36-38].”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [37]
In the citing paper
“It has been suggested that during activities involving sustained muscle contractions or higher intensity exercises, the contact between the device’s PPG sensor and skin is decreased, leading to a disruption in the signal quality and causing poor quality data [36,37].”
From Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study (2018) · cites this paper as [37]
In the citing paper
“Firstly, surface EMG, increased electrode impedance, respiration induced baseline drift, and electrode contact movement can cause noise and motion artifacts.88”
From Wearable sensors for monitoring the physiological and biochemical profile of the athlete (2019) · cites this paper as [88]
In the citing paper
“However, the intrinsic PPG disturbances originating from physiological processes, such as respiration, vasoconstriction due to temperature changes or stress [57], have not been considered.”
From Modeling of artifacts in the wrist photoplethysmogram: Application to the detection of life-threatening arrhythmias (2021) · cites this paper as [57]
In the citing paper
“The photoplethysmogram (PPG) signal is a measure of arterial blood volume, which fluctuates with each heartbeat and is used by many wearables to monitor heart rate (HR).”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“The mechanisms underlying the PPG pulse wave shape are not yet fully understood [6].”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“The shape is influenced not only by the incident wave transmitted through the arteries from the heart but also by reflected waves from a range of arterial sites [6].”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“Cardiac output, monitored in peri-operative and critical care settings, has been estimated from pulse wave shape and low-frequency PPG variations”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [6]
In the citing paper
“Thus, while the pulsating components of PPG are related to arterial blood volume, the non-pulsating component is a function of the average blood volume, respiration, the sympathetic nervous system, and thermoregulation [151].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [151]
In the citing paper
“These more recent wearable physical activity devices, which include a measure of heart rate, utilize photoplethysmography (PPG) to measure heart rate.”
From Estimating Accuracy at Exercise Intensities: A Comparative Study of Self-Monitoring Heart Rate and Physical Activity Wearable Devices (2017) · cites this paper as [17]
In the citing paper
“PPG is a simple and low-cost optical technique that detects blood volume changes in the microvascular bed of tissue [17].”
From Estimating Accuracy at Exercise Intensities: A Comparative Study of Self-Monitoring Heart Rate and Physical Activity Wearable Devices (2017) · cites this paper as [17]
Citations
Cites
(1992) · Applied Ergonomics · doi:10.1016/0003-6870(92)90338-v · Cited by 7,153
Non-invasive detection of endothelial dysfunction in children and adults at risk of atherosclerosis
Celermajer, D. S., Sorensen, K. E., Gooch, V. M., Spiegelhalter, D. J., Miller, O. I., Sullivan, I. D., Lloyd, J. K., & Deanfield, J. E. (1992) · The Lancet · doi:10.1016/0140-6736(92)93147-f · Cited by 4,742
Anderson, R. R., & Parrish, J. A. (1981) · Journal of Investigative Dermatology · doi:10.1111/1523-1747.ep12479191 · Cited by 2,456
An Introduction to Medical Statistics.
(1931) · JAMA · doi:10.1001/jama.1931.02730150055037 · Cited by 2,085
Avolio, A. P., Chen, S. G., Wang, R. P., Zhang, C. L., Li, M., & OʼRourke, M. F. (1983) · Circulation · doi:10.1161/01.cir.68.1.50 · Cited by 965
Investigation of Chronic Venous Insufficiency: A Consensus Statement
Nicolaides, A. N. (2000) · Circulation · doi:10.1161/01.cir.102.20.e126 · Cited by 945
Duck, F. A. (1990) · Cited by 854
Fifteen years experience with finger arterial pressure monitoring: assessment of the technology
Imholz, B. P. M. (1998) · Cardiovascular Research · doi:10.1016/s0008-6363(98)00067-4 · Cited by 841
Assessment of cardiac output from systemic arterial pressure in humans
Romano, S. M., & Pistolesi, M. (2002) · Critical Care Medicine · doi:10.1097/00003246-200208000-00027 · Cited by 634
Determination of age-related increases in large artery stiffness by digital pulse contour analysis
Millasseau, S., Kelly, R. P., Ritter, J., & Chowienczyk, P. (2002) · Clinical Science · doi:10.1042/cs1030371 · Cited by 624
Research works printed but not linked: 37
- Abramowitz H B, 1979, Surgery, 86, 434
- Agache P G, 1994, Acta. Derm. Venereol. Suppl. (Stockholm), 185, 47
- Aoyagi T Kiahi M Yamaguchi K Watanabe S, 1974, Abstracts of the 13th Annual Meeting of the Japanese Society of Medical Electronics and Biological Engineering, 90
- Aoyagi T, 2002, Anesth. Analg., 94, 51
- Barnes R W, 1991, Circulation, 83, I20
- Dutch J, 1983, N. Z. Med. J., 96, 607
- Evans M L, 1988, Med. Instrum., 22, 29
- Grohmann G, 1996, Perfusion, 9, 268
- Grohmann G, 1996, Perfusion, 9, 300
- Grossmann K, 1987, VASA, 16, 324
- Hanzlik P J, 1936, J. Pharmac. Exp. Ther., 56, 194
- Heck A F, 1975, Med. Instrum., 9, 88
- Hertzer N R, 1991, Circulation, 83, I12
- Hertzman A B, 1963, Aerospace Med., 34, 710
- Hertzman A B, 1937, Am. J. Physiol., 119, 334
- Hirai M, 1977, VASA, 6, 215
- Incze A, 2003, Rom. J. Int. Med., 41, 35
- Lane I F, 1984, Hosp. Update, 861
- 10.1023/A:1016942504084 · DOI
- Lee B Y, 1979, Surg. Gynecol. Obstet., 148, 233
- Miwa Z, 2002, Pediatr. Dent., 24, 594
- Molitor H, 1936, J. Pharmacol. Exp. Ther., 57, 6
- Nielsen P E, 1973, VASA, 2, 65
- Ochoa W, 1980, J. Exp. Med., 132, 413
- Oliva I, 1976, VASA, 5, 95
- Peñáz J, 1973, Digest 10th Int Conf. Med. Biol. Eng., 104
- Peñáz J, 1978, Automedica, 2, 135
- Porret C A, 1995, Am. J. Physiol., 269, H1852
- Ruiz-Vega H, 1998, Proc. West Pharmacol. Soc., 41, 73
- Shusterman V, 1997, Am. J. Physiol., 273, R1173
- Simonson E, 1956, Geriatrics, 11, 425
- Sophromadze Z, 2006, Georgian Med. News, 133, 72
- 10.1023/A:1016936206694 · DOI
- Weinman J, 1972, T-I-T J. Life Sci., 2, 121
- Weng J, 1998, Biomed. Tech., 43, 92
- Zheng D, 2006, Comput. Cardiol., 33, 289
- Zheng D C Zhang Y T, 2003, Proc. 25th Annual International Conf. of the IEEE EMBC, 4, 3184
Cited by
Sorted by citations
Remote plethysmographic imaging using ambient light
Verkruysse, W., Svaasand, L. O., & Nelson, J. S. (2008) · Optics Express · doi:10.1364/oe.16.021434 · Cited by 1,728
Non-contact, automated cardiac pulse measurements using video imaging and blind source separation
Poh, M., McDuff, D., & Picard, R. W. (2010) · Optics Express · doi:10.1364/oe.18.010762 · Cited by 1,652
Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam
Poh, M., McDuff, D., & Picard, R. W. (2010) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2010.2086456 · Cited by 1,514
Wearable sensors: modalities, challenges, and prospects
Heikenfeld, J., Jajack, A., Rogers, J., Gutruf, P., Tian, L., Pan, T., Li, R., Khine, M., Kim, J., Wang, J., et al. (2018) · Lab on a Chip · doi:10.1039/c7lc00914c · Cited by 1,434
Wearable Sensors for Remote Health Monitoring
Majumder, S., Mondal, T., & Deen, M. (2017) · Sensors · doi:10.3390/s17010130 · Cited by 1,375
Bio-Integrated Wearable Systems: A Comprehensive Review
Ray, T. R., Choi, J., Bandodkar, A. J., Krishnan, S., Gutruf, P., Tian, L., Ghaffari, R., & Rogers, J. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00573 · Cited by 1,350
Choong, C., Shim, M., Lee, B., Jeon, S., Ko, D., Kang, T., Bae, J., Lee, S. H., Byun, K., Im, J., et al. (2014) · Advanced Materials · doi:10.1002/adma.201305182 · Cited by 1,249
On the Analysis of Fingertip Photoplethysmogram Signals
Elgendi, M. (2012) · Current Cardiology Reviews · doi:10.2174/157340312801215782 · Cited by 1,206
Lim, H., Kim, H. S., Qazi, R., Kwon, Y., Jeong, J., & Yeo, W. (2019) · Advanced Materials · doi:10.1002/adma.201901924 · Cited by 1,013
Ghamari, M. (2018) · International Journal of Biosensors & Bioelectronics · doi:10.15406/ijbsbe.2018.04.00125 · Cited by 945
Toward ubiquitous blood pressure monitoring via pulse transit time: Theory and practice
Mukkamala, R., Hahn, J.-O., Inan, O. T., Mestha, L. K., Kim, C.-S., Toreyin, H., & Kyal, S. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2441951 · Cited by 935
“The advantage of reflectance-mode PPG is that it is less restrictive in terms of measurement locations [66], [67], [69].”
BackgroundMethodWearable photoplethysmographic sensors—past and present
Tamura, T., Maeda, Y., Sekine, M., & Yoshida, M. (2014) · Electronics · doi:10.3390/electronics3020282 · Cited by 912
Organic Photodetectors for Next‐Generation Wearable Electronics
Chow, P. C. Y., & Someya, T. (2019) · Advanced Materials · doi:10.1002/adma.201902045 · Cited by 778
Zhang, Z., Pi, Z., & Liu, B. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2359372 · Cited by 759
How accurate is pulse rate variability as an estimate of heart rate variability?
Schäfer, A., & Vagedes, J. (2013) · International Journal of Cardiology · doi:10.1016/j.ijcard.2012.03.119 · Cited by 661
The use of photoplethysmography for assessing hypertension
Elgendi, M., Fletcher, R., Liang, Y., Howard, N., Lovell, N. H., Abbott, D., Lim, K., & Ward, R. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0136-7 · Cited by 625
Human Emotion Recognition: Review of Sensors and Methods
Dzedzickis, A., Kaklauskas, A., & Bučinskas, V. (2020) · Sensors · doi:10.3390/s20030592 · Cited by 628
Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging
Sun, Y., & Thakor, N. V. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2476337 · Cited by 589
Henriksen, A., Haugen Mikalsen, M., Woldaregay, A. Z., Muzny, M., Hartvigsen, G., Hopstock, L. A., & Grimsgaard, S. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9157 · Cited by 542
Wearable sensors for monitoring the physiological and biochemical profile of the athlete
Seshadri, D. R., Li, R. T., Voos, J. E., Rowbottom, J. R., Alfes, C. M., Zorman, C. A., & Drummond, C. K. (2019) · npj Digital Medicine · doi:10.1038/s41746-019-0150-9 · Cited by 537
Improved motion robustness of remote-PPG by using the blood volume pulse signature
de Haan, G., & van Leest, A. (2014) · Physiological Measurement · doi:10.1088/0967-3334/35/9/1913 · Cited by 491
A High‐Performance Solution‐Processed Organic Photodetector for Near‐Infrared Sensing
Huang, J., Lee, J., Vollbrecht, J., Брус, В. В., Dixon, A. L., Cao, D. X., Zhu, Z., Du, Z., Wang, H., Cho, K., et al. (2019) · Advanced Materials · doi:10.1002/adma.201906027 · Cited by 492
Gil, E., Orini, M., Bailón, R., Vergara, J. M., Mainardi, L., & Laguna, P. (2010) · Physiological Measurement · doi:10.1088/0967-3334/31/9/015 · Cited by 461
Large-area low-noise flexible organic photodiodes for detecting faint visible light
Fuentes‐Hernandez, C., Chou, W.-F., Khan, T. M., Diniz, L., Lukens, J., Larrain, F. A., Rodriguez-Toro, V. A., & Kippelen, B. J. (2020) · Science · doi:10.1126/science.aba2624 · Cited by 446
Photoplethysmogram Analysis and Applications: An Integrative Review
Park, J., Seok, H. S., Kim, S.-S., & Shin, H. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2021.808451 · Cited by 514
Contact-Based Methods for Measuring Respiratory Rate
Massaroni, C., Nicolò, A., Presti, D. L., Sacchetti, M., Silvestri, S., & Schena, E. (2019) · Sensors · doi:10.3390/s19040908 · Cited by 465
DistancePPG: Robust non-contact vital signs monitoring using a camera
Kumar, M., Veeraraghavan, A., & Sabharwal, A. (2015) · Biomedical Optics Express · doi:10.1364/boe.6.001565 · Cited by 417
Measuring pulse rate with a webcam — A non-contact method for evaluating cardiac activity
Lewandowska, M., Rumiński, J., Kocejko, T., & Nowak, J. (2011) · Cited by 420
Zhang, Z. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2406332 · Cited by 388
Blood Pressure Estimation from Photoplethysmogram Using a Spectro-Temporal Deep Neural Network
Slapničar, G., Mlakar, N., & Luštrek, M. (2019) · Sensors · doi:10.3390/s19153420 · Cited by 387
The impact of wearable technologies in health research: scoping review
Huhn, S., Axt, M., Gunga, H.-C., Maggioni, M. A., Munga, S., Obor, D., Sié, A., Boudo, V., Bunker, A., Sauerborn, R., et al. (2022) · JMIR mHealth and uHealth · doi:10.2196/34384 · Cited by 379
Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review
Charlton, P. H., Birrenkott, D. A., Bonnici, T., Pimentel, M. A. F., Johnson, A. E. W., Alastruey, J., Tarassenko, L., Watkinson, P. J., Beale, R., & Clifton, D. A. (2018) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2017.2763681 · Cited by 379
Back to the Future: Achieving Health Equity Through Health Informatics and Digital Health
Brewer, L. C., Fortuna, K. L., Jones, C., Walker, R., Hayes, S. N., Patten, C. A., & Cooper, L. A. (2020) · JMIR mHealth and uHealth · doi:10.2196/14512 · Cited by 367
Tulyakov, S., Alameda-Pineda, X., Ricci, E., Yin, L., Cohn, J. F., & Sebe, N. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.263 · Cited by 351
Self-powered cardiovascular electronic devices and systems
Zheng, Q., Tang, Q., Wang, Z. L., & Li, Z. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-020-0426-4 · Cited by 348
Diode fibres for fabric-based optical communications
Rein, M., Favrod, V. D., Hou, C., Khudiyev, T., Stolyarov, A. M., Cox, J. R., Chung, C., Chhav, C., Ellis, M., Joannopoulos, J. D., et al. (2018) · Nature · doi:10.1038/s41586-018-0390-x · Cited by 344
Selvaraj, N., Jaryal, A. K., Santhosh, J., Deepak, K. K., & Anand, S. (2008) · Journal of Medical Engineering & Technology · doi:10.1080/03091900701781317 · Cited by 342
Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring
Fine, J., Branan, K. L., Rodriguez, A. J., Boonya-ananta, T., Ajmal, Ramella-Roman, J. C., McShane, M. J., & Coté, G. L. (2021) · Biosensors · doi:10.3390/bios11040126 · Cited by 348
Intelligence in the Internet of Medical Things era: A systematic review of current and future trends
Al-Turjman, F. M., Nawaz, M. H., & Uluşar, Ü. D. (2019) · Computer Communications · doi:10.1016/j.comcom.2019.12.030 · Cited by 338
The psychophysiology of flow during piano playing.
de Manzano, Ö., Theorell, T., Harmat, L., & Ullén, F. (2010) · Emotion · doi:10.1037/a0018432 · Cited by 330
Non-contact heart rate and heart rate variability measurements: A review
Kranjec, J., Beguš, S., Geršak, G., & Drnovšek, J. (2014) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2014.03.004 · Cited by 332
Baek, H. J., Cho, C.-H., Cho, J., & Woo, J. (2015) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2014.0104 · Cited by 317
Monte-Moreno, E. (2011) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2011.05.001 · Cited by 311
Remote measurement of cognitive stress via heart rate variability
McDuff, D., Gontarek, S., & Picard, R. W. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6944243 · Cited by 325
Avolio, A. P., Butlin, M., & Walsh, A. (2009) · Physiological Measurement · doi:10.1088/0967-3334/31/1/r01 · Cited by 309
Photoplethysmography based atrial fibrillation detection: a review
Pereira, T., Tran, N., Gadhoumi, K., Pelter, M. M., Do, D. H., Lee, R. J., Colorado, R., Meisel, K., & Hu, X. (2020) · npj Digital Medicine · doi:10.1038/s41746-019-0207-9 · Cited by 300
Flexible graphene photodetectors for wearable fitness monitoring
Polat, E. O., Mercier, G., Nikitskiy, I., Puma, E., Galán, T., Gupta, S., Marques, M. M., Piqueras, J. J., Bouwens, M., Durduran, T., et al. (2019) · Science Advances · doi:10.1126/sciadv.aaw7846 · Cited by 301
El-Hajj, C., & Kyriacou, P. A. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.101870 · Cited by 300
Accurate Heart Rate Monitoring During Physical Exercises Using PPG
Temko, A. (2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2676243 · Cited by 295
Biswas, D., Everson, L. R., Liu, M., Panwar, M., Verhoef, B.-E., Patki, S., Kim, C. H., Acharyya, A., Hoof, C. A. V., Konijnenburg, M., et al. (2019) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2019.2892297 · Cited by 312
Advances in Photopletysmography Signal Analysis for Biomedical Applications
Moraes, J. L., Rocha, M. X., Vasconcelos, G. G., Vasconcelos Filho, J. E., De Albuquerque, V. H. C., & Alexandria, A. R. (2018) · Sensors · doi:10.3390/s18061894 · Cited by 292
Wearable Sensing Technology Applications in Construction Safety and Health
Ahn, C. R., Lee, S. H., Sun, C., Jebelli, H., Yang, K., & Choi, B. (2019) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0001708 · Cited by 319
Recent Progress on Broadband Organic Photodetectors and their Applications
Zhao, Z., Xu, C., Niu, L., Zhang, X., & Zhang, F. (2020) · Laser & Photonics Review · doi:10.1002/lpor.202000262 · Cited by 290
Improvements in Remote Cardiopulmonary Measurement Using a Five Band Digital Camera
McDuff, D., Gontarek, S., & Picard, R. W. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2323695 · Cited by 290
Lee, H., Kim, E., Lee, Y., Kim, H., Lee, J., Kim, M., Yoo, H., & Yoo, S. (2018) · Science Advances · doi:10.1126/sciadv.aas9530 · Cited by 279
Dynamic time warping and machine learning for signal quality assessment of pulsatile signals
Li, Q., & Clifford, G. D. (2012) · Physiological Measurement · doi:10.1088/0967-3334/33/9/1491 · Cited by 274
Heart Rate Estimation From Wrist-Worn Photoplethysmography: A Review
Biswas, D., Simões‐Capela, N., Hoof, C. A. V., & Helleputte, N. V. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2914166 · Cited by 273
Charlton, P. H., Harana, J. M., Vennin, S., Li, Y., Chowienczyk, P., & Alastruey, J. (2019) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00218.2019 · Cited by 269
Chowdhury, M. H., Shuzan, M. N. I., Chowdhury, M. E. H., Mahbub, Z. B., Uddin, M. M., Khandakar, A., & Reaz, M. B. I. (2020) · Sensors · doi:10.3390/s20113127 · Cited by 276
New principle for measuring arterial blood oxygenation, enabling motion-robust remote monitoring
van Gastel, M., Stuijk, S., & de Haan, G. (2016) · Scientific Reports · doi:10.1038/srep38609 · Cited by 253
Li, S., Wang, H., Ma, W., Qiu, L., Xia, K., Zhang, Y., Lü, H., Zhu, M., Liang, X., Wu, X., et al. (2023) · Science Advances · doi:10.1126/sciadv.adh0615 · Cited by 265
Wearable Photoplethysmography for Cardiovascular Monitoring
Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3149785 · Cited by 250
Current progress of photoplethysmography and SPO2 for health monitoring
TAMURA, T. (2019) · Biomedical Engineering Letters · doi:10.1007/s13534-019-00097-w · Cited by 274
A new look at the essence of the imaging photoplethysmography
Kamshilin, A. A., Nippolainen, E., Sidorov, I. S., Васильев, П. В., Ерофеев, Н. П., Podolyan, N. P., & Владимирович, Р. Р. (2015) · Scientific Reports · doi:10.1038/srep10494 · Cited by 250
Chan, P., Wong, C., Poh, Y. C., Pun, L., Leung, W. W., Wong, Y., Wong, M. M., Poh, M., Chu, D. W., & Siu, C. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.116.003428 · Cited by 240
Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review
Georgiou, K., Larentzakis, A. V., Khamis, N. N., Alsuhaibani, G. I., Alaska, Y. A., & Giallafos, E. J. (2018) · Folia Medica · doi:10.2478/folmed-2018-0012 · Cited by 244
Webb, R. C., Ma, Y., Krishnan, S. R., Li, Y., Yoon, S. P., Guo, X., Feng, X., Shi, Y., Seidel, M., Cho, N. H., et al. (2015) · Science Advances · doi:10.1126/sciadv.1500701 · Cited by 247
An optimal filter for short photoplethysmogram signals
Liang, Y., Elgendi, M., Chen, Z., & Ward, R. (2018) · Scientific Data · doi:10.1038/sdata.2018.76 · Cited by 242
Physiological and Behavioral Responses Reveal 9-Month-Old Infants’ Sensitivity to Pleasant Touch
Fairhurst, M. T., Löken, L. S., & Großmann, T. (2014) · Psychological Science · doi:10.1177/0956797614527114 · Cited by 250
Dooley, E. E., Golaszewski, N. M., & Bartholomew, J. B. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.7043 · Cited by 242
Wearable Devices for Physical Monitoring of Heart: A Review
Prieto-Avalos, G., Cruz-Ramos, N. A., Alor‐Hernández, G., Sánchez-Cervantes, J. L., Rodríguez-Mazahua, L., & Guarneros-Nolasco, L. R. (2022) · Biosensors · doi:10.3390/bios12050292 · Cited by 275
Quigley, K. S., Gianaros, P. J., Norman, G. J., Jennings, J. R., Berntson, G. G., & de Geus, E. J. C. (2024) · Psychophysiology · doi:10.1111/psyp.14604 · Cited by 281
Blood pressure estimation from appropriate and inappropriate PPG signals using A whole-based method
Mousavi, S. S., Firouzmand, M., Charmi, M., Hemmati, M. R., Moghadam, M., & Ghorbani, Y. (2018) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2018.08.022 · Cited by 234
Heart rate variability with photoplethysmography in 8 million individuals: a cross-sectional study
Natarajan, A., Pantelopoulos, A., Emir-Farinas, H., & Natarajan, P. (2020) · The Lancet Digital Health · doi:10.1016/s2589-7500(20)30246-6 · Cited by 229
Flexible Organic Transistors for Biosensing: Devices and Applications
Song, J., Liu, H., Zhao, Z., Lin, P., & Yan, F. (2023) · Advanced Materials · doi:10.1002/adma.202300034 · Cited by 233
Cuff-Less and Continuous Blood Pressure Monitoring: A Methodological Review
Sharma, M., Barbosa, K., Ho, V., Griggs, D., Ghirmai, T., Krishnan, S., Hsiai, T., Chiao, J.-C., & Cao, H. (2017) · Technologies · doi:10.3390/technologies5020021 · Cited by 226
A Rigid-Flex Wearable Health Monitoring Sensor Patch for IoT-Connected Healthcare Applications
Wu, T., Wu, F., Qiu, C., Redouté, J., & Yuce, M. R. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2977164 · Cited by 230
Greene, S., Thapliyal, H., & Caban‐Holt, A. (2016) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2016.2590178 · Cited by 237
A review of signals used in sleep analysis
Roebuck, A., Monasterio, V., Gederi, E., Osipov, M., Behar, J. A., Malhotra, A., Penzel, T., & Clifford, G. D. (2013) · Physiological Measurement · doi:10.1088/0967-3334/35/1/r1 · Cited by 234
Kim, K. B., & Baek, H. J. (2023) · Electronics · doi:10.3390/electronics12132923 · Cited by 260
Garbarino, M., Lai, M., Tognetti, S., Picard, R. W., & Bender, D. (2014) · Wireless Mobile Communication and Healthcare · doi:10.4108/icst.mobihealth.2014.257418 · Cited by 215
A new, short-recorded photoplethysmogram dataset for blood pressure monitoring in China
Liang, Y., Chen, Z., Liu, G., & Elgendi, M. (2018) · Scientific Data · doi:10.1038/sdata.2018.20 · Cited by 215
Sun, Y., Hu, S., Azorin-Peris, V., Chambers, J. A., Zhu, Y., & Greenwald, S. E. (2011) · Journal of Biomedical Optics · doi:10.1117/1.3602852 · Cited by 213
A survey of remote optical photoplethysmographic imaging methods
McDuff, D., Estepp, J. R., Piasecki, A. M., & Blackford, E. B. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319857 · Cited by 212
Adaptive threshold method for the peak detection of photoplethysmographic waveform
Shin, H. S., Lee, C., & Lee, M. (2009) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2009.10.006 · Cited by 211
The advantages of wearable green reflected photoplethysmography
Maeda, Y., Sekine, M., & Tamura, T. (2011) · Journal of Medical Systems · doi:10.1007/s10916-010-9506-z · Cited by 209
Schuurmans, A. A. T., de Looff, P., Nijhof, K. S., Rosada, C., Scholte, R. H. J., Popma, A., & Otten, R. (2020) · Journal of Medical Systems · doi:10.1007/s10916-020-01648-w · Cited by 210
Kushki, A., Drumm, E., Pla Mobarak, M., Tanel, N., Dupuis, A., Chau, T., & Anagnostou, E. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059730 · Cited by 209
Microvascular imaging: techniques and opportunities for clinical physiological measurements
Allen, J., & Howell, K. J. (2014) · Physiological Measurement · doi:10.1088/0967-3334/35/7/r91 · Cited by 208
Self-citationHuman Vital Signs Detection Methods and Potential Using Radars: A Review
Kebe, M., Gadhafi, R., Mohammad, B. S., Sanduleanu, M., Saleh, H. H., & Al‐Qutayri, M. (2020) · Sensors · doi:10.3390/s20051454 · Cited by 229
Maeda, Y., Sekine, M., & Tamura, T. (2011) · Journal of Medical Systems · doi:10.1007/s10916-010-9505-0 · Cited by 203
Transducer Technologies for Biosensors and Their Wearable Applications
Polat, E. O., Çetin, M. M., Tabak, A. F., Güven, E. B., Uysal, B. Ö., Arsan, T., Kabbani, A., Hamed, H., & GÜL, S. B. (2022) · Biosensors · doi:10.3390/bios12060385 · Cited by 215
Lee, J., Matsumura, K., Yamakoshi, K.-I., Rolfe, P., Tanaka, S., & Yamakoshi, T. (2013) · 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6609852 · Cited by 202
Sleep Staging Based on Signals Acquired Through Bed Sensor
Kortelainen, J., Mendez, M. O., Bianchi, A. M., Matteucci, M., & Cerutti, S. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2010.2044797 · Cited by 202
Chen, S., Wu, N., Lin, S., Duan, J., Xu, Z., Pan, Y., Zhang, H., Xu, Z., Huang, L., Hu, B., et al. (2020) · Nano Energy · doi:10.1016/j.nanoen.2020.104460 · Cited by 196
The 2023 wearable photoplethysmography roadmap
Charlton, P. H., Allen, J., Bailón, R., Baker, S., Behar, J. A., Chen, F., Clifford, G. D., Clifton, D. A., Davies, H. J., Ding, C., et al. (2023) · Physiological Measurement · doi:10.1088/1361-6579/acead2 · Cited by 233
Self-citationFlexible Doppler ultrasound device for the monitoring of blood flow velocity
Wang, F., Jin, P., Feng, Y., Fu, J. S., Wang, P., Liu, X., Zhang, Y., Ma, Y., Yang, Y., Yang, A., et al. (2021) · Science Advances · doi:10.1126/sciadv.abi9283 · Cited by 204
Diagnostic Features and Potential Applications of PPG Signal in Healthcare: A Systematic Review
Almarshad, M. A., Islam, M. S., Al-Ahmadi, S. A., & BaHammam, A. S. (2022) · Healthcare · doi:10.3390/healthcare10030547 · Cited by 215
Motion-tolerant magnetic earring sensor and wireless earpiece for wearable photoplethysmography
Poh, M., Swenson, N. C., & Picard, R. W. (2010) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2010.2042607 · Cited by 189
Remote heart rate measurement using low-cost RGB face video: a technical literature review
Rouast, P. V., Adam, M., Chiong, R., Cornforth, D., & Lux, E. (2018) · Frontiers of Computer Science · doi:10.1007/s11704-016-6243-6 · Cited by 188
Metadata
- Authors
- Allen, J.
- Affiliations
- Freeman Hospital (GB)
- Corresponding author
- Allen, John
- ORCID
- Allen, John
- Venue
- Physiological Measurement
- Publisher
- IOP Publishing
- Published
- 2007-02-20
- Volume
- 28
- Issue
- 3
- Pages
- R1-R39
- ISSN
- 0967-3334 (ISSN-L)
- 1361-6579
- OpenAlex
- W2083872334
- Cited by
- 3,967
- References
- 275
- Citations by year
- 2026: 308 · 2025: 292 · 2024: 310 · 2023: 317 · 2022: 323 · 2021: 314 · 2020: 291 · 2019: 304 · 2018: 299 · 2017: 227 · 2016: 185 · 2015: 216 · 2014: 159 · 2013: 132 · 2012: 86
- FWCI
- 3.44
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Physiological Measurement (publishedVersion)
- PubMed (publishedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Surgery › Hemodynamic Monitoring and Therapy
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Disease Prevention
- Keywords
- photoplethysmography, blood volume changes, pulse wave analysis, non-invasive physiological monitoring, oxygen saturation, blood pressure measurement, cardiac output, autonomic function, peripheral vascular disease, vascular assessment, light-tissue interaction
- MeSH terms
- Autonomic Nervous System, Blood Vessels, Humans, Monitoring, Physiologic, Vascular Diseases, Photoplethysmography
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
