Analysis of a Pulse Rate Variability Measurement Using a Smartphone Camera
Open accessAbstract
Background. Heart rate variability (HRV) provides information about the activity of the autonomic nervous system. Because of the small amount of data collected, the importance of HRV has not yet been proven in clinical practice. To collect population-level data, smartphone applications leveraging photoplethysmography (PPG) and some medical knowledge could provide the means for it. Objective. To assess the capabilities of our smartphone application, we compared PPG (pulse rate variability (PRV)) with ECG (HRV). To have a baseline, we also compared the differences among ECG channels. Method. We took fifty parallel measurements using iPhone 6 at a 240 Hz sampling frequency and Cardiax PC-ECG devices. The correspondence between the PRV and HRV indices was investigated using correlation, linear regression, and Bland-Altman analysis. Results. High PPG accuracy: the deviation of PPG-ECG is comparable to that of ECG channels. Mean deviation between PPG-ECG and two ECG channels: RR: 0.01 ms–0.06 ms, SDNN: 0.78 ms–0.46 ms, RMSSD: 1.79 ms–1.21 ms, and pNN50: 2.43%–1.63%. Conclusions. Our iPhone application yielded good results on PPG-based PRV indices compared to ECG-based HRV indices and to differences among ECG channels. We plan to extend our results on the PPG-ECG correspondence with a deeper analysis of the different ECG channels.
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Cites
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
Martin Bland, J., & Altman, D. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90837-8 · Cited by 47,965 · see citing works
Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use
Electrophysiology, T. F. O. T. E. S. O. C. T. N. A. (1996) · Circulation · doi:10.1161/01.cir.93.5.1043 · Cited by 17,159 · see citing works
Heart rate variability: Standards of measurement, physiological interpretation, and clinical use
Malik, M., Bigger, J. T., Camm, A. J., Kleiger, R. E., Malliani, A., Moss, A. J., & Schwartz, P. J. (1996) · European Heart Journal · doi:10.1093/oxfordjournals.eurheartj.a014868 · Cited by 15,289 · see citing works
Statistics corner: A guide to appropriate use of correlation coefficient in medical research.
(2012) · Europe PMC (PubMed Central) · Cited by 4,239 · see citing works
Understanding bland altman analysis
Giavarina, D. (2015) · Biochemia Medica · doi:10.11613/bm.2015.015 · Cited by 4,022 · see citing works
Sassi, R., Cerutti, S., Lombardi, F., Malik, M., Huikuri, H. V., Peng, C.-K., Schmidt, G., Yamamoto, Y., Reviewers:, D., Gorenek, B., et al. (2015) · Europace · doi:10.1093/europace/euv015 · Cited by 727 · see citing works
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 · cited 3× · see citing works
“PRV and HRV have good correlations, and it was con fi rmed by several previous publications [9 – 11].”
BackgroundResultI. Using the Bland–Altman method to measure agreement with repeated measures
Myles, P. S., & Cui, J. (2007) · British Journal of Anaesthesia · doi:10.1093/bja/aem214 · Cited by 620 · see citing works
Lau, J. K., Lowres, N., Neubeck, L., Brieger, D. B., Sy, R. W., Galloway, C. D., Albert, D. E., & Freedman, S. B. (2013) · International Journal of Cardiology · doi:10.1016/j.ijcard.2013.01.220 · Cited by 326 · see citing works
Role of editing of R–R intervals in the analysis of heart rate variability
Peltola, M. A. (2012) · Frontiers in Physiology · doi:10.3389/fphys.2012.00148 · Cited by 306 · see citing works
Bilchick, K. C., & Berger, R. D. (2006) · Journal of Cardiovascular Electrophysiology · doi:10.1111/j.1540-8167.2006.00501.x · Cited by 183 · see citing works
Desteghe, L., Raymaekers, Z., Lutin, M., Vijgen, J. M., Dilling-Boer, D. M., Koopman, P., Schurmans, J., Vanduynhoven, P., Dendale, P., & Heidbüchel, H. (2016) · EP Europace · doi:10.1093/europace/euw025 · Cited by 171 · see citing works
Extraction of Heart Rate Variability from Smartphone Photoplethysmograms
Peng, R., Zhou, X.-L., Lin, W.-H., & Zhang, Y. (2015) · Computational and Mathematical Methods in Medicine · doi:10.1155/2015/516826 · Cited by 152 · see citing works
A Real Time Analysis of PPG Signal for Measurement of SpO2 and Pulse Rate
Bagha, S., & Shaw, L. (2011) · International Journal of Computer Applications · Cited by 143 · see citing works
Comparison of HRV parameters derived from photoplethysmography and electrocardiography signals
Jeyhani, V., Mahdiani, S., Peltokangas, M., & Vehkaoja, A. T. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319747 · Cited by 136 · see citing works
Linear and Nonlinear Heart Rate Variability Indexes in Clinical Practice
Buccelletti, F., Bocci, M. G., Emanuele, G., Valentina, F., Sara, C. J., Fragnoli, C., Maviglia, R., & Francesco, F. (2012) · Computational and Mathematical Methods in Medicine · doi:10.1155/2012/219080 · Cited by 129 · see citing works
Heathers, J. A. J. (2013) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2013.05.017 · Cited by 122 · see citing works
Smartphone ECG for evaluation of STEMI: Results of the ST LEUIS Pilot Study
Muhlestein, J. B., Le, V. T., Albert, D. J., Moreno, F. L., Anderson, J. L., Yanowitz, F. G., Vranian, R. B., Barsness, G. W., Bethea, C. F., Severance, H. W., et al. (2014) · Journal of Electrocardiology · doi:10.1016/j.jelectrocard.2014.11.005 · Cited by 85 · see citing works
Stöckl, D., Rodríguez Cabaleiro, D., Van Uytfanghe, K., & Thienpont, L. M. (2004) · Clinical Chemistry · doi:10.1373/clinchem.2004.036095 · Cited by 79 · see citing works
Matsumura, K., Rolfe, P. J., Lee, J., & Yamakoshi, T. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091205 · Cited by 72 · see citing works
A Pulse Rate Estimation Algorithm Using PPG and Smartphone Camera
Siddiqui, S. A., Zhang, Y., Feng, Z., & Kos, A. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0485-6 · Cited by 57 · see citing works
Esco, M. R., Flatt, A. A., & Nakamura, F. Y. (2016) · The Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000001519 · Cited by 50 · see citing works
Yan, B. P., Chan, C. K., Li, C. K., To, O. T., Lai, W. H., Tse, G., Poh, Y. C., & Poh, M.-Z. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.7275 · Cited by 50 · see citing works
Bolea, J., Pueyo, E., Orini, M., & Bailón, R. (2016) · Frontiers in Physiology · doi:10.3389/fphys.2016.00501 · Cited by 37 · see citing works
da Silva, A. K. F., Christófaro, D. G. D., Bernardo, A. F. B., Vanderlei, F. M., & Vanderlei, L. C. M. (2017) · Arquivos Brasileiros de Cardiologia · doi:10.5935/abc.20170024 · Cited by 30 · see citing works
Heart Rate Variability Fraction—A New Reportable Measure of 24‐Hour R‐R Interval Variation
Sosnowski, M., Clark, E., Latif, S., Macfarlane, P. W., & Tendera, M. (2005) · Annals of Noninvasive Electrocardiology · doi:10.1111/j.1542-474x.2005.00579.x · Cited by 27 · see citing works
Evaluation of agreement between temporal series obtained from electrocardiogram and pulse wave.
Leikan, G. M., Rossi, E., Sanz, M., Delisle-Rodríguez, D., Mantaras, M. C., Nicolet, J., Zapata, D., Lapyckyj, I., Siri, L. N., & Perrone, M. (2016) · Journal of Physics Conference Series · doi:10.1088/1742-6596/705/1/012038 · Cited by 8 · see citing works
Low-cost photoplethysmograph solutions using the Raspberry Pi
Nagy, T., & Gingl, Z. (2013) · IEEE International Symposium on Computational Intelligence and Informatics (CINTI) · doi:10.1109/cinti.2013.6705184 · Cited by 7 · see citing works
Self-citationLoading, Plotting, and Filtering RR Intervals
Martínez, C. A. G., Quintana, A. O., Vila, X. A., Touriño, M. J. L., Rodrı́guez-Liñares, L., Presedo, J., & Méndez, A. J. (2017) · Use R! · doi:10.1007/978-3-319-65355-6_2 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- [22]Lin G. H. Chang Y. H. Lin K. P. Comparison of heart rate variability measured by ECG in different signal lengths Journal of Medical and Biological Engineering 2005 25 2 67 71
- [25]Clifford G. D. Signal processing methods for heart rate variability, [Ph.D. thesis] 2002 University of Oxford
- [26]Drijkoningen L. Lenaerts F. Van der Auwera J. Validation of a smartphone based photoplethysmographic beat detection algorithm for normal and ectopic complexes Computing in Cardiology 2014 2014 Cambridge, MA, USA 845 848
Cited by
Sorted by citations
Smartphone Sensors for Health Monitoring and Diagnosis
Majumder, S., & Deen, M. J. (2019) · Sensors · doi:10.3390/s19092164 · Cited by 440 · see citing works
khan, Z. F., & Alotaibi, S. R. (2020) · Journal of Healthcare Engineering · doi:10.1155/2020/8894694 · Cited by 235 · see citing works
Anikwe, C. V., Nweke, H. F., Ikegwu, A. C., Egwuonwu, C. A., Onu, F. U., Alo, U. R., & Teh, Y. W. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.117362 · Cited by 250 · see citing works
Continuous Monitoring of Vital Signs Using Cameras: A Systematic Review
Vinothini, S., Spicher, N., Wang, J., Ganapathy, N., Warnecke, J. M., Leonhardt, S. K., Swaminathan, R., & Deserno, T. M. (2022) · Sensors · doi:10.3390/s22114097 · Cited by 122 · see citing works
Stone, J. D., Ulman, H. K., Tran, K., Thompson, A. G., Halter, M. D., Ramadan, J. H., Stephenson, M., Finomore, V. S., Galster, S. M., Rezai, A. R., et al. (2021) · Frontiers in Sports and Active Living · doi:10.3389/fspor.2021.585870 · Cited by 95 · see citing works
Mullick, T., Radović, A., Shaaban, S., & Doryab, A. (2022) · JMIR Formative Research · doi:10.2196/35807 · Cited by 85 · see citing works
Béres, S., & Hejjel, L. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102589 · Cited by 70 · see citing works
Member, I., Pernice, R., Javorka, M., Krohová, J., Czippelová, B., Turianiková, Z., Busacca, A., & Faes, L. (2019) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-019-01957-4 · Cited by 66 · see citing works
Taha, A. R., Shehadeh, M., Alshehhi, A., Altamimi, T., Housser, E., Simsekler, M. C. E., Alfalasi, B., Memari, S. A., Hosani, F. I. A., Zaabi, Y. A., et al. (2022) · PLoS ONE · doi:10.1371/journal.pone.0264436 · Cited by 57 · see citing works
Peak Detection and HRV Feature Evaluation on ECG and PPG Signals
Esgalhado, F., Batista, A. G., Vassilenko, V., Russo, S., & Ortigueira, M. D. (2022) · Symmetry · doi:10.3390/sym14061139 · Cited by 52 · see citing works
Heart rate variability based physical exertion monitoring for manual material handling tasks
Umer, W., Yu, Y., Antwi‐Afari, M. F., Li, J., Siddiqui, M. K., & Li, H. (2022) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2022.103301 · Cited by 40 · see citing works
Liu, I., Ni, S., & Peng, K. (2020) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2019.0283 · Cited by 36 · see citing works
Kumar, C. K., Manaswini, M., Maruthy, K. N., Kumar, A. V. S., & kumar, K. M. (2021) · Clinical Epidemiology and Global Health · doi:10.1016/j.cegh.2021.100698 · Cited by 34 · see citing works
Reddy, G. N. K., Manikandan, M. S., Murty, N. V. L. N., & Cenkeramaddi, L. R. (2023) · IEEE Access · doi:10.1109/access.2023.3269584 · Cited by 32 · see citing works
Taeger, J., Bischoff, S., Hagen, R., & ten Rak, K. (2020) · JMIR mhealth and uhealth · doi:10.2196/19346 · Cited by 29 · see citing works
Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach
Liu, I., Ni, S., & Peng, K. (2020) · Sensors · doi:10.3390/s20071923 · Cited by 26 · see citing works
Pernice, R., Faes, L., Kotiuchyi, I., Stivala, S. S., Busacca, A., Popov, A. O., & Kharytonov, V. (2019) · Physiological Measurement · doi:10.1088/1361-6579/ab16a3 · Cited by 24 · see citing works
Guede-Fernández, F., Ferrer-Mileo, V., Mateu-Mateus, M., Ramos-Castro, J. J., Garcia-Gonzalez, M. A., & Fernández-Chimeno, M. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.101717 · Cited by 24 · see citing works
Measurement of Cancer-Related Fatigue Based on Heart Rate Variability: Observational Study
Shih, C., Chou, P.-C., Chou, T.-L., & Huang, T. (2021) · Journal of Medical Internet Research · doi:10.2196/25791 · Cited by 23 · see citing works
Gambassi, B. B., Neves, V. R., de Brito, E. Z. A., Fernandes, D. S. D. S., Sá, C. A., Nogueira, R. M. D. R., Almeida, F. D. J. F., Cavalcanti, P. A. D. A., Silva, D. C. G. G. E., Neto, D. S., et al. (2020) · PubMed Central · Cited by 19 · see citing works
The Effect of the Menstrual Cycle on Daily Measures of Heart Rate Variability in Athletic Women
Kokts‐Porietis, R. L., Minichiello, N. R., & Doyle–Baker, P. K. (2019) · Journal of Psychophysiology · doi:10.1027/0269-8803/a000237 · Cited by 16 · see citing works
Tecco, A. D., Pistolesi, F., & Lazzerini, B. (2024) · IEEE Access · doi:10.1109/access.2024.3362668 · Cited by 15 · see citing works
Mather, J. D., Hayes, L. D., Mair, J. L., & Sculthorpe, N. F. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1326511 · Cited by 17 · see citing works
Using Rear Smartphone Cameras as Sensors for Measuring Heart Rate Variability
Zhang, G., Zhang, S., Dai, Y., & Shi, B. (2021) · IEEE Access · doi:10.1109/access.2021.3054065 · Cited by 15 · see citing works
Ajtay, B. E., Béres, S., & Hejjel, L. (2022) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2022.104033 · Cited by 15 · see citing works
A Wearable Electrocardiography Armband Resilient Against Artifacts
Zhou, Y., Mohaddes, F., Lee, C., Rao, S., Mills, A. C., Curry, A. C., Lee, B., & Misra, V. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3197060 · Cited by 13 · see citing works
Stress Detection Using Smartphone Extracted Photoplethysmography
Panganiban, F. C., & de Leon, F. A. (2021) · IEEE Region 10 Symposium (TENSYMP) · doi:10.1109/tensymp52854.2021.9550905 · Cited by 13 · see citing works
Does stress induction affect cognitive performance or avoidance of cognitive effort?
Picciotto, G., & Fabio, R. A. (2023) · Stress and Health · doi:10.1002/smi.3280 · Cited by 12 · see citing works
Gingl, Z., Makan, G., Mellár, J., Vadai, G., & Mingesz, R. (2019) · IEEE Access · doi:10.1109/access.2019.2926519 · Cited by 12 · see citing works
Self-citationTabor, A., Bateman, S., Scheme, E., & schraefel, M. C. (2022) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.926649 · Cited by 11 · see citing works
Reddy, G. N. K., Manikandan, M. S., & Murty, N. V. L. N. (2021) · IEEE International Conference on Health, Instrumentation & Measurement, and Natural Sciences (InHeNce) · doi:10.1109/inhence52833.2021.9537236 · Cited by 11 · see citing works
Aristizabal, J.-P., Navegantes, R. E. S., Melo, E., & Pereira, A. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.572191 · Cited by 11 · see citing works
Liu, Y., Guo, X., & Zhang, Y. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105461 · Cited by 10 · see citing works
SaECG: a new FHIR Data format revision to enable continuous ECG storage and monitoring
Benhamida, A., Kanas, A., Vincze, M., Papp, K. T., Abbassi, M., & Kozlovszky, M. (2020) · IEEE International Symposium on Computational Intelligence and Informatics (CINTI) · doi:10.1109/cinti51262.2020.9305828 · Cited by 10 · see citing works
Sinha, M. K., Vaishali, K., Maiya, A. G., Shivashankar, K. N., & Shashikiran, U. (2023) · F1000Research · doi:10.12688/f1000research.139283.1 · Cited by 10 · see citing works
Problems in archiving long-term continuous ECG data – a review
Benhamida, A., ZOUAOUI, A., Szocska, G., Karóczkai, K., SLIMANI, G., & Kozlovszky, M. (2019) · IEEE World Symposium on Applied Machine Intelligence and Informatics (SAMI) · doi:10.1109/sami.2019.8782737 · Cited by 10 · see citing works
Human ECG data collection, digitalization, streaming and storing
Benhamida, A., & Kozlovszky, M. (2020) · IEEE World Symposium on Applied Machine Intelligence and Informatics (SAMI) · doi:10.1109/sami48414.2020.9108765 · Cited by 9 · see citing works
Pramanik, H. S., Pal, A., Kirtania, M., Chakravarty, T., & Ghose, A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823696-3.00018-0 · Cited by 8 · see citing works
A validity and reliability study of Conditional Entropy Measures of Pulse Rate Variability
Pernice, R., Javorka, M., Krohová, J., Czippelová, B., Turianiková, Z., Busacca, A., & Faes, L. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856594 · Cited by 8 · see citing works
Pernice, R., Parisi, A., Guarino, S., Fallica, G., Vinciguerra, V., Ferla, G., Faes, L., & Busacca, A. (2020) · IEEE Mediterranean Electrotechnical Conference (MELECON) · doi:10.1109/melecon48756.2020.9140716 · Cited by 7 · see citing works
Sivaranjini, P. N., & Manikandan, M. S. (2023) · International Conference on Bio-engineering for Smart Technologies (BioSMART) · doi:10.1109/biosmart58455.2023.10162081 · Cited by 7 · see citing works
Health Status Prediction with Local-Global Heterogeneous Behavior Graph
Ma, X., Yang, X., Gao, J., & Xu, C. (2021) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3457893 · Cited by 7 · see citing works
Batista, L. H. R., Domingues, W. J. R., Silva, A. D. A. C. E., Lopes, K. A. T., Amorim, M. L. D. C., & Rossato, M. F. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102845 · Cited by 6 · see citing works
Sivaranjini, P. N., Manikandan, M. S., & Cenkeramaddi, L. R. (2023) · International Conference on Electronics, Computers and Artificial Intelligence (ECAI) · doi:10.1109/ecai58194.2023.10194196 · Cited by 6 · see citing works
Digital physiological biomarkers predict within-person symptom changes in complex chronic illness
Brandes-Aitken, A. N., Sawyer, A., Iwasaki, A., Krumholz, H. M., Preston, R., Calcraft, P., Leeming, H., Tosto, J., Proal, A. D., Osborne, M. A., et al. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-02543-3 · Cited by 5 · see citing works
Farhan, A., Mouhsen, A., Labakoum, B., Rattal, M., & Lyazidi, A. (2024) · Biomedical & Pharmacology Journal · doi:10.13005/bpj/2873 · Cited by 5 · see citing works
Predicting Personality with Smartphone Cameras: A Pilot Study
Liu, I., Ni, S., & Peng, K. (2020) · IEEE International Conference on Human-Machine Systems (ICHMS) · doi:10.1109/ichms49158.2020.9209354 · Cited by 5 · see citing works
Quintanar-Gómez, J., Robles-Camarillo, D., Trejo-Macotela, F. R., & Campero-Jurado, I. (2021) · IEEE Latin America Transactions · doi:10.1109/tla.2021.9461853 · Cited by 5 · see citing works
Sivaranjini, P. N., Manikandan, M. S., & Cenkeramaddi, L. R. (2023) · IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) · doi:10.1109/icsima59853.2023.10373442 · Cited by 4 · see citing works
Ajtay, B. E., Béres, S., & Hejjel, L. (2023) · Applied Sciences · doi:10.3390/app13095642 · Cited by 3 · see citing works
Тащук, В. К., Tashchuk, M. V., & Іванчук, П. Р. (2019) · Clinical & experimental pathology · doi:10.24061/1727-4338.xviii.2.68.2019.14 · Cited by 3 · see citing works
Effects of electrocardiographic noise on ultra-short term Heart Rate Variability indices
Raimondi, A., Busacca, A., Giaconia, G. C., Antonacci, Y., Stivala, S. S., Faes, L., & Pernice, R. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110803 · Cited by 2 · see citing works
Ahamad, S. (2025) · Biomedical Materials & Devices · doi:10.1007/s44174-025-00378-2 · Cited by 2 · see citing works
Low cost Electronic Instrumentation Solutions for Cardiovascular Parameters Measurement
Acef, L., BOUZERGUI, F., Benouar, S., Hafid, A., & Ferroukhi, M. (2019) · International Conference on Advanced Electrical Engineering (ICAEE) · doi:10.1109/icaee47123.2019.9014818 · Cited by 1 · see citing works
Pulluri, K. K., Manikandan, M. S., Sivaranjini, P. N., & Pachori, R. B. (2023) · IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA) · doi:10.1109/icsima59853.2023.10373496 · Cited by 1 · see citing works
Deepa, H. S., & Das, R. (2021) · Indian Journal Of Applied Research · doi:10.36106/ijar/6214476 · Cited by 1 · see citing works
Device for measuring heart rate parameters and generating radio-physical feedback signals.
Kobrisev, P. A., Korjenevsky, A. V., & Черепенин, В. А. (2021) · Journal of Radio Electronics · doi:10.30898/1684-1719.2021.6.12 · Cited by 1 · see citing works
Heart Rate Analysis through Smartphone Camera
Sabatini, A., Iannello, G., Pennazza, G., Santonico, M., Spinosa, M., & Vollero, L. (2021) · IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) · doi:10.1109/metroind4.0iot51437.2021.9488509 · Cited by 1 · see citing works
Pulse Rate Estimation with a Smartphone Camera Using Image Processing Algorithm
Sowmiya, E. C., Nirmala, K., & Suganthi, L. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-5936-3_28 · Cited by 1 · see citing works
Design of a Photoplethysmography Signal Qualifier: A Geometric Approach for Mobile ApplicationsPreprint
Almeida, A., Canais, F., Maçorano, R., Lopes, M. L., Ferreira, H. A., & Brás, S. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4942633 · Cited by 1 · see citing works
Reducing Pulse Rate Variability Computational Error from a 30 Hz Photoplethysmography Recording
Panganiban, F. C., & de Leon, F. A. (2019) · International Symposium on Multimedia and Communication Technology (ISMAC) · doi:10.1109/ismac.2019.8836186
Das, R., Kataria, S., Sharma, P., Janakiraman, K., Shrivastava, M., & Mahadevappa, G. (2021) · INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH · doi:10.36106/ijsr/4315612
Mather, J. D., Sculthorpe, N. F., Mair, J. L., & Hayes, L. D. (2024) · doi:10.2196/preprints.66662
MC-EVM: A Movement-Compensated EVM Algorithm with Face Detection for Remote Pulse Monitoring
Benhamida, A., & Kozlovszky, M. (2025) · Applied Sciences · doi:10.3390/app15031652
Smartphone Sensor‐Based Physiological Parameter Monitoring: Advances, Apps, and Discussions
Li, S., Wang, M., Xiong, J., Li, X., Du, J., Ji, N., & Chen, J. (2025) · Expert Systems · doi:10.1111/exsy.70068
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Heart rate variability in COMISA: toward autonomic phenotyping for precision sleep medicine
Sabil, A., & Pengo, M. F. (2026) · SLEEP · doi:10.1093/sleep/zsag126
Müller-Graff, F.-T., Essig, F., Friedrich, M. U., Hoika, K., Hackenberg, S., Rak, K., & Taeger, J. (2026) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/81963
- Authors
- Bánhalmi, A., Borbás, J., Fidrich, M., Bilicki, V., Gingl, Z., & Rudas, L.
- Affiliations
- University of Szeged (HU)
- Corresponding author
- Bánhalmi, András
- Venue
- Journal of Healthcare Engineering
- Publisher
- Wiley
- Published
- 2018
- Volume
- 2018
- Pages
- 1-15
- ISSN
- 2040-2295 (ISSN-L)
- 2040-2309
- PMC
- PMC5832098
- OpenAlex
- W2794220693
- Cited by
- 69
- References
- 29
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 5 · 2023: 10 · 2022: 9 · 2021: 15 · 2020: 10 · 2019: 11 · 2018: 1
- FWCI
- 3.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Healthcare Engineering (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- SZTE Publicatio Repozitórium (University of Szeged) (acceptedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- European Regional Development Fund
- European Union
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- pulse rate variability, heart rate variability, photoplethysmography, smartphone camera, mobile application, ECG comparison, autonomic nervous system, RR interval, SDNN, RMSSD, pNN50
- MeSH terms
- Smartphone, Adult, Electrocardiography, Female, Heart Rate, Humans, Male, Pulse, Signal Processing, Computer-Assisted, Photoplethysmography
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