Relationship Between Measurement Site and Motion Artifacts in Wearable Reflected Photoplethysmography
Abstract
Pulse rates obtained from wearable photoplethysmography (PPG) sensors are important for monitoring cardiovascular condition, especially during exercise. However, it is difficult to precisely count pulse rates during exercise because PPG is sensitive to body movement. The artifacts from body movement are caused by a change in the blood volume at the measurement site, in addition to pulsatile changes. Here, we investigated the influence of motion artifact with respect to light source and anatomical sites. In this study, we compared the signal from green-light PPG to that from infrared PPG at different anatomical sites. In these experiments, 11 subjects were asked to either assume a resting position or generate spontaneous motion artifact by jumping and swinging their arm. As a result, pulse rates obtained from green-light PPG showed a higher correlation with the ECG R-R interval as compared to those obtained with infrared. Additionally, the signal from the upper arm showed less artifact than did the peripheral one. Therefore, the green-light PPG may be useful for pulse rate monitoring.
Integrity signals
Registry
Cites
Statistics
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?
Intensity-linked improvements are modest rather than decisive, but suggest that PPG systems may perform comparatively better when stroke volume and pulsatility increase.
“We therefore interpret intensity-linked improvements as modest rather than decisive, but they do suggest that PPG systems may perform comparatively better when stroke volume and pulsatility increase [2,29].”
From PPG-Based Heart Rate Accuracy in Hispanic Adults with Fitzpatrick III–V Skin Tones: An Evaluation of Body Composition and Skin-Tone Effects (2026) · cites this paper as [29]
The Mio Alpha has displayed more accurate measurement of heart rate in conjunction with an accelerometer compared to an infrared heart rate system when compensating for movement artifacts.
“and has displayed more accurate measurement of heart rate in conjunction with an accelerometer compared to an infrared heart rate system when compensating for movement artifacts (Maeda, Sekine, Tamura, 2011b).”
From Examining the Role of Implicit Emotional Judgments in Social Anxiety and Experiential Avoidance (2017) · cites this paper as Maeda, Sekine, Tamura, 2011b
Motion artifacts are a primary cause of bad signal quality.
“Motion artifacts are a primary cause of bad signal quality, and research has suggested various methods for mitigating these26,39,40.”
From Data quality evaluation in wearable monitoring (2022) · cites this paper as [39]
Artifact characteristics from finger oximetry and neck PPG cannot be straightforwardly transferred to simulating wrist PPG because distinct body locations have different tissue optical properties for different wavelengths and are prone to specific interference.
“Nevertheless, these artifact characteristics cannot be straightforwardly transferred to simulating the wrist PPG since distinct body locations have different tissue optical properties for different wavelengths and are prone to specific interference [54].”
From Modeling of artifacts in the wrist photoplethysmogram: Application to the detection of life-threatening arrhythmias (2021) · cites this paper as [54]
Alternative measurement sites such as the arm, ear, chest, or face can have advantages over the wrist, including being less prone to motion artifact or vasoconstriction and providing more accurate heart rate measurements.
“These alternative sites can have advantages over the wrist, such as being less prone to motion artifact [63] or vasoconstriction [62], and providing more accurate HR measurements [64].”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [63]
During sedentary moments, respiration rate, thermoregulation, and sympathetic nervous system activity cause the DC baseline to wander.
“During sedentary moments, respiration rate, thermoregulation, and sympathetic nervous system activity cause the DC baseline to wander [162].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [162]
The green sensor had a lower artifact ratio for all locations compared to the IR sensor.
“The green sensor also had a lower artifact ratio for all locations compared to the IR sensor.”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [162]
Red and IR have deeper penetration depths than blue and green, making them prone to more motion artifacts such as factors that directly affect the DC baseline.
“With their longer wavelengths, red and IR have deeper penetration depths compared to blue and green, making them prone to more motion artifacts such as the factors that directly affect the DC baseline [162,164].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [162]
The highest correlation coefficient between the PPG signal and a chest ECG was that of the green sensor on the upper arm.
“The highest correlation coefficient between the PPG signal and a chest ECG was that of the green sensor on the upper arm.”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [162]
The upper arm had the lowest artifact ratio among upper arm, forearm, wrist, and finger.
“They found the upper arm had the lowest artifact ratio, which is the ratio of the magnitude of the PPG signal after a motion and the magnitude of the PPG signal before the motion.”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [162]
Cites
Photoplethysmography and its application in clinical physiological measurement
Allen, J. (2007) · Physiological Measurement · doi:10.1088/0967-3334/28/3/r01 · Cited by 3,967 · see citing works
THE BLOOD SUPPLY OF VARIOUS SKIN AREAS AS ESTIMATED BY THE PHOTOELECTRIC PLETHYSMOGRAPH
Hertzman, A. B. (1938) · American Journal of Physiology-Legacy Content · doi:10.1152/ajplegacy.1938.124.2.328 · Cited by 455 · see citing works
Motion Artifact Reduction in Photoplethysmography Using Independent Component Analysis
Kim, B., & Yoo, S. K. (2006) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2005.869784 · Cited by 400 · see citing works
Skin photoplethysmography — a review
Kamal, A. A. R., Harness, J. B., Irving, G., & Mearns, A. J. (1989) · Computer Methods and Programs in Biomedicine · doi:10.1016/0169-2607(89)90159-4 · Cited by 328 · see citing works
Basal perfusion of the cutaneous microcirculation: Measurements as a function of anatomic position
Tur, E., Tur, M., Maibach, H. I., & Guy, R. H. (1983) · Journal of Investigative Dermatology · doi:10.1111/1523-1747.ep12522619 · Cited by 163 · see citing works
Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution
Yan, Y. S., Poon, C. C. Y., & Zhang, Y. (2005) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-2-3 · Cited by 157 · see citing works
Regional Differences in the Basal and Maximal Rates of Blood Flow in the Skin
Hertzman, A. B., & Randall, W. C. (1948) · Journal of Applied Physiology · doi:10.1152/jappl.1948.1.3.234 · Cited by 92 · see citing works
Variability of photoplethysmographyperipheral pulse measurementsat the ears, thumbs and toes
Allen, J., & Murray, A. (2000) · IEE Proceedings - Science Measurement and Technology · doi:10.1049/ip-smt:20000846 · Cited by 76 · see citing works
Artifact reduction in photoplethysmography
Hayes, M., & Smith, P. R. (1998) · Applied Optics · doi:10.1364/ao.37.007437 · Cited by 71 · see citing works
Kalman Filter Based Adaptive Reduction Of Motion Artifact From Photoplethysmographic Signal
Seyedtabaii, S., & Seyedtabaii, L. (2008) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1333655 · Cited by 59 · see citing works
RELATIONS BETWEEN CUTANEOUS BLOOD FLOW AND BLOOD CONTENT IN THE FINGER PAD, FOREARM, AND FOREHEAD
Hertzman, A. B., Randall, W. C., & Jochim, K. E. (1947) · American Journal of Physiology-Legacy Content · doi:10.1152/ajplegacy.1947.150.1.122 · Cited by 27 · see citing works
Flagged first, then by citations
1 of the 12 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
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 · see citing works
Wearable photoplethysmographic sensors—past and present
Tamura, T., Maeda, Y., Sekine, M., & Yoshida, M. (2014) · Electronics · doi:10.3390/electronics3020282 · Cited by 912 · see citing works
“In recent years, different measurement sites for PPG sensors have been explored extensively, including the ring finger [14], wrist [15,16], brachia [9,17,18], earlobe [19–21], external ear cartilage [22–24], and the superior auricular region [25–27].”
BackgroundSelf-citationMonitoring of the central blood pressure waveform via a conformal ultrasonic device
Wang, C., Li, X., Hu, H., Zhang, L., Huang, Z., Lin, M., Zhang, Z., Yin, Z., Huang, B., Gong, H., et al. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0287-x · Cited by 895 · see citing works
Zhang, Z. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2406332 · Cited by 388 · see citing works
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 · see citing works
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 · see citing works
Current progress of photoplethysmography and SPO2 for health monitoring
TAMURA, T. (2019) · Biomedical Engineering Letters · doi:10.1007/s13534-019-00097-w · Cited by 260 · see citing works
Self-citationJinno, H., Yokota, T., Koizumi, M., Yukita, W., Saito, M., Osaka, I., Fukuda, K., & Someya, T. (2021) · Nature Communications · doi:10.1038/s41467-021-22558-6 · Cited by 253 · see citing works
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 · see citing works
Hartmann, V., Liu, H., Chen, F., Qiu, Q., Hughes, S., & Zheng, D. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2019.00198 · Cited by 173 · see citing works
Salehizadeh, S. M. A., Dao, D. K., Bolkhovsky, J., Cho, C. H., Mendelson, Y., & Chon, K. H. (2015) · Sensors · doi:10.3390/s16010010 · Cited by 173 · see citing works
A Review of Wearable Multi-Wavelength Photoplethysmography
Ray, D., Collins, T., Woolley, S., & Ponnapalli, P. (2023) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2021.3121476 · Cited by 155 · see citing works
Longmore, S. K., Lui, G. Y., Naik, G. R., Breen, P. P., Jalaludin, B. B., & Gargiulo, G. D. (2019) · Sensors · doi:10.3390/s19081874 · Cited by 133 · see citing works
Min, S., An, J., Lee, J. H., Kim, J. H., Joe, D. J., Eom, S. H., Yoo, C. D., Ahn, H., Hwang, J.-Y., Xu, S. H., et al. (2025) · Nature Reviews Cardiology · doi:10.1038/s41569-025-01127-0 · Cited by 132 · see citing works
Scardulla, F., Cosoli, G., Spinsante, S., Poli, A., Iadarola, G., Pernice, R., Busacca, A., Pasta, S., Scalise, L., & D’Acquisto, L. (2023) · Measurement · doi:10.1016/j.measurement.2023.113150 · Cited by 120 · see citing works
Wearable and implantable biosensors: mechanisms and applications in closed-loop therapeutic systems
Zheng, Z., Zhu, R., Peng, I., Xu, Z., & Jiang, Y. (2024) · Journal of Materials Chemistry B · doi:10.1039/d4tb00782d · Cited by 114 · see citing works
Wearable Photoplethysmography for Cardiovascular Monitoring.
Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · KTUePubl (Repository of Kaunas University of Technology) · doi:10.17863/cam.81148 · Cited by 113 · see citing works
Wearable devices for continuous monitoring of biosignals: Challenges and opportunities
Stuart, T., Hanna, J., & Gutruf, P. (2022) · APL Bioengineering · doi:10.1063/5.0086935 · Cited by 114 · see citing works
Ye, Y., Cheng, Y., He, W., Hou, M., & Zhang, Z. (2016) · IEEE Sensors Journal · doi:10.1109/jsen.2016.2597265 · Cited by 94 · see citing works
Data quality evaluation in wearable monitoring
Böttcher, S., Vieluf, S., Bruno, E., Joseph, B., Epitashvili, N., Biondi, A., Zabler, N., Glasstetter, M., Dümpelmann, M., Van Laerhoven, K., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-25949-x · Cited by 91 · see citing works
Sensors Capabilities, Performance, and Use of Consumer Sleep Technology
de Zambotti, M., Cellini, N., Menghini, L., Sarlo, M., & Baker, F. C. (2020) · Sleep Medicine Clinics · doi:10.1016/j.jsmc.2019.11.003 · Cited by 88 · 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
Wearable Sensor System to Monitor Physical Activity and the Physiological Effects of Heat Exposure
Pham, S., Yeap, D., Escalera, G., Basu, R., Wu, X., Kenyon, N. J., Hertz‐Picciotto, I., Ko, M., & Davis, C. E. (2020) · Sensors · doi:10.3390/s20030855 · Cited by 70 · see citing works
Simone, G., Tordera, D., Delvitto, E., Peeters, B., van Breemen, A. J. J. M., Meskers, S. C. J., Janssen, R. A. J., & Gelinck, G. H. (2020) · Advanced Optical Materials · doi:10.1002/adom.201901989 · Cited by 64 · see citing works
Sartor, F., Gelissen, J., van Dinther, R., Roovers, D., Papini, G. B., & Coppola, G. (2018) · BMC Sports Science, Medicine and Rehabilitation · doi:10.1186/s13102-018-0098-0 · Cited by 65 · see citing works
A Robust Fusion Method for Motion Artifacts Reduction in Photoplethysmography Signal
Nabavi, S. K., & Bhadra, S. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2020.3006636 · Cited by 60 · see citing works
Validation of a Photoplethysmographic Heart Rate Monitor: Polar OH1
Hermand, E., Cassirame, J., Ennequin, G., & Hue, O. (2019) · International Journal of Sports Medicine · doi:10.1055/a-0875-4033 · Cited by 59 · see citing works
Susana, E., Ramli, K., Murfi, H., & Apriantoro, N. H. (2022) · Information · doi:10.3390/info13020059 · Cited by 59 · see citing works
Grubb, M., Carpenter, J., Crowe, J. A., Teoh, J. Y., Marlow, N., Ward, C., Mann, C., Sharkey, D., & Hayes‐Gill, B. (2014) · Physiological Measurement · doi:10.1088/0967-3334/35/5/881 · Cited by 56 · see citing works
In-Ear Pulse Rate Measurement: A Valid Alternative to Heart Rate Derived from Electrocardiography?
Passler, S., Müller, N., & Senner, V. (2019) · Sensors · doi:10.3390/s19173641 · Cited by 55 · see citing works
Wrist-Worn Hand Gesture Recognition While Walking via Transfer Learning
Kang, P., Li, J., Fan, B., Jiang, S., & Shull, P. B. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2021.3100099 · Cited by 55 · see citing works
Cuffless Blood Pressure in clinical practice: challenges, opportunities and current limits.
Henry, B., Merz, M., Hoang, H., Abdulkarim, G., Wosik, J., & Schoettker, P. (2024) · Blood Pressure · doi:10.1080/08037051.2024.2304190 · Cited by 54 · see citing works
Li, J., Chu, H., Chen, Z., Yiu, C. K., Qu, Q., Li, Z.-Y., & Yu, X. (2024) · ACS Nano · doi:10.1021/acsnano.4c04291 · Cited by 50 · see citing works
A Review of Noninvasive Methodologies to Estimate the Blood Pressure Waveform
Athaya, T., & Choi, S. (2022) · Sensors · doi:10.3390/s22103953 · Cited by 51 · see citing works
Convertino, V. A., Schauer, S. G., Weitzel, E. K., Cardin, S., Stackle, M. E., Talley, M. J., Sawka, M. N., & Inan, O. T. (2020) · Sensors · doi:10.3390/s20226413 · Cited by 49 · see citing works
Virtual reality sickness detection: an approach based on physiological signals and machine learning
Martin, N., Mathieu, N., Pallamin, N., Ragot, M., & Diverrez, J.-M. (2020) · Proceedings - International Symposium on Mixed and Augmented Reality, ISMAR · doi:10.1109/ismar50242.2020.00065 · Cited by 50 · see citing works
Validity of heart rate measurements by the Garmin Forerunner 225 at different walking intensities
Claes, J., Buys, R., Ávila, A., Finlay, D., Kennedy, A., Guldenring, D., Budts, W., & Cornelissen, V. (2017) · Journal of Medical Engineering & Technology · doi:10.1080/03091902.2017.1333166 · Cited by 49 · see citing works
A Review of Methods for Non-Invasive Heart Rate Measurement on Wrist
De Pinho Ferreira, N., Gehin, C., & Massot, B. (2021) · IRBM · doi:10.1016/j.irbm.2020.04.001 · Cited by 49 · see citing works
Sañudo, B., De Hoyo, M., Muñoz-López, A., Perry, J., & Abt, G. (2019) · Journal of Medical Systems · doi:10.1007/s10916-019-1325-2 · Cited by 48 · see citing works
Liu, H., Allen, J., Khalid, S. G., Chen, F., & Zheng, D. (2021) · Physiological Measurement · doi:10.1088/1361-6579/ac0a34 · Cited by 50 · see citing works
Gong, S. P., Yap, L. W., Zhang, Y., He, J., Yin, J., Marzbanrad, F., Kaye, D. M., & Cheng, W. (2022) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2022.114072 · Cited by 48 · see citing works
Application of Optical Heart Rate Monitoring
Lemay, M., Bertschi, M., Solà, J., Renevey, P., Parák, J., & Korhonen, I. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-418662-0.00023-4 · Cited by 46 · see citing works
Xu, K., Jiang, X., & Chen, W. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2960370 · Cited by 46 · see citing works
Landry, C., Peterson, S. D., & Arami, A. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.2967759 · Cited by 43 · see citing works
Nardelli, M., Vanello, N., Galperti, G., Greco, A., & Scilingo, E. P. (2020) · Sensors · doi:10.3390/s20113156 · Cited by 43 · see citing works
Is Continuous Heart Rate Monitoring of Livestock a Dream or Is It Realistic? A Review
Nie, L., Berckmans, D., Wang, C., & Li, B. (2020) · Sensors · doi:10.3390/s20082291 · Cited by 43 · see citing works
Comparison of Green, Blue and Infrared Light in Wrist and Forehead Photoplethysmography
Vizbara, V. (2013) · Cited by 40 · see citing works
Dur, O., Rhoades, C. E., Ng, M. S., Elsayed, R., van Mourik, R. A., & Majmudar, M. D. (2018) · JMIR mhealth and uhealth · doi:10.2196/11040 · Cited by 38 · see citing works
Zhou, C., Feng, J., Hu, J. H., & Ye, X. (2015) · Journal of Medical Systems · doi:10.1007/s10916-015-0412-2 · Cited by 38 · see citing works
Xu, K., Jiang, X., Lin, S., Dai, C., & Chen, W. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.2988097 · Cited by 37 · see citing works
Validity of Ultra-Short-Term HRV Analysis Using PPG—A Preliminary Study
Taoum, A., Bisiaux, A., Tilquin, F., Guillou, Y. L., & Carrault, G. (2022) · Sensors · doi:10.3390/s22207995 · Cited by 37 · see citing works
Determinants of photoplethysmography signal quality at the wrist
Charlton, P. H., Marozas, V., Mejía‐Mejía, E., Kyriacou, P. A., & Mant, J. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000585 · Cited by 38 · see citing works
Kim, J., Kim, J.-H., & Ko, H. (2015) · Sensors · doi:10.3390/s16010046 · Cited by 36 · see citing works
Accurate Blood Pressure Estimation During Activities of Daily Living: A Wearable Cuffless Solution
Landry, C., Hedge, E. T., Hughson, R. L., Peterson, S. D., & Arami, A. (2021) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2021.3054597 · Cited by 36 · see citing works
Zhang, Y., Gu, T., Luo, C., Kostakos, V., & Seneviratne, A. P. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3191788 · Cited by 34 · see citing works
Effects of skin surface temperature on photoplethysmograph
Jeong, I. C., Yoon, H., Kang, H., & Yeom, H. (2014) · Journal of Healthcare Engineering · doi:10.1260/2040-2295.5.4.429 · Cited by 33 · see citing works
Lam, E., Aratia, S., Wang, J., & Tung, J. Y. (2020) · JMIR Biomedical Engineering · doi:10.2196/17355 · Cited by 33 · see citing works
A Survey of Photoplethysmography and Imaging Photoplethysmography Quality Assessment Methods
Desquins, T., Bousefsaf, F., Pruski, A., & Maaoui, C. (2022) · Applied Sciences · doi:10.3390/app12199582 · Cited by 33 · see citing works
Optical heart rate monitoring module validation study
Valenti, G., & Westerterp, K. R. (2013) · 2013 IEEE International Conference on Consumer Electronics (ICCE) · doi:10.1109/icce.2013.6486856 · Cited by 32 · see citing works
Accuracy and Reliability of Pulse O2 Saturation Measured by a Wrist-worn Oximeter
Hermand, É., Coll, C., Richalet, J., & Lhuissier, F. (2021) · International Journal of Sports Medicine · doi:10.1055/a-1337-2790 · Cited by 31 · see citing works
Study of a Ring-Type Surgical Pleth Index Monitoring System Based on Flexible PPG Sensor
Zhou, C., Wang, H., Zhang, Y., & Ye, X. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3041072 · Cited by 29 · see citing works
Real time heart rate detection from PPG signal in noisy environment
Das, S., Pal, S., & Mitra, M. (2016) · International Conference on Intelligent Control Power and Instrumentation (ICICPI) · doi:10.1109/icicpi.2016.7859676 · Cited by 27 · see citing works
Matsumura, K., Toda, S., & Kato, Y. (2020) · IEEE Access · doi:10.1109/access.2020.2990438 · Cited by 27 · see citing works
Advances in Photoplethysmography for Personalized Cardiovascular Monitoring
Kim, S., Xiao, X., & Chen, J. (2022) · Biosensors · doi:10.3390/bios12100863 · Cited by 25 · see citing works
Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review
Lü, L., Zhu, T., Morelli, D., Creagh, A. P., Liu, Z., Yang, J., Liu, F., Zhang, Y., & Clifton, D. A. (2023) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2023.3271595 · Cited by 28 · see citing works
Paliakaitė, B., Petrėnas, A., Sološenko, A., & Marozas, V. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102421 · Cited by 24 · see citing works
Gagnon, J., Khau, M., Lavoie-Hudon, L., Vachon, F., Drapeau, V., & Tremblay, S. (2022) · JMIR Formative Research · doi:10.2196/37885 · Cited by 22 · see citing works
Cugmas, B., Štruc, E., & Spīgulis, J. (2018) · Physiological Measurement · doi:10.1088/1361-6579/aaf433 · Cited by 24 · see citing works
Wang, C.-F., Wang, T.-Y., Kuo, P.-H., Wang, H., Li, S.-Z., Lin, C., Chan, S.-C., Liu, T., Lo, Y., Lin, S.-H., et al. (2023) · Biosensors · doi:10.3390/bios13030321 · Cited by 24 · see citing works
Indoor Self‐Powered Perovskite Optoelectronics with Ultraflexible Monochromatic Light Source
Jinno, H., Shivarudraiah, S. B., Rasmussen, A., Vagli, G., Marcato, T., Eickemeyer, F. T., Pfeifer, L., Yokota, T., Someya, T., & Shih, C. (2023) · Advanced Materials · doi:10.1002/adma.202304604 · Cited by 23 · see citing works
Volpes, G., Valenti, S., Genova, G., Barà, C., Parisi, A., Faes, L., Busacca, A., & Pernice, R. (2024) · Biosensors · doi:10.3390/bios14040205 · Cited by 23 · see citing works
Rational selection of RGB channels for disease classification based on IPPG technology
Xu, G., Dong, L., Yuan, J., Zhao, Y., Liu, M., Hui, M., Zhao, Y., & Kong, L. (2022) · Biomedical Optics Express · doi:10.1364/boe.451736 · Cited by 22 · see citing works
Characterization of Artifact Signals in Neck Photoplethysmography
García-López, I., & Rodriguez–Villegas, E. (2020) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2020.2972378 · Cited by 22 · see citing works
Intelligent sensing devices and systems for personalized mental health
Xing, Y., Yang, Y., Yang, K., Lu, A., Xing, L., Mackie, K., & Guo, F. (2025) · Med-X · doi:10.1007/s44258-025-00057-3 · Cited by 14 · see citing works
Puranen, A., Halkola, T., Kirkeby, O., & Vehkaoja, A. T. (2020) · Proceedings of IEEE Sensors/Proceedings of IEEE Sensors ... · doi:10.1109/sensors47125.2020.9278523 · Cited by 19 · see citing works
Fabric‐Based Ultrasonic Sensor with Integrated Piezoelectric Composite for Blood Pressure Monitoring
Li, B., Wang, T., Luo, D., Peng, P., Wang, Y., Liu, L., Wang, H., & Liu, H. (2023) · Advanced Materials Technologies · doi:10.1002/admt.202201814 · Cited by 19 · see citing works
Validity of the Polar Vantage M watch when measuring heart rate at different exercise intensities
Shumate, T., Link, M., Furness, J. W., Kemp‐Smith, K., Simas, V., & Climstein, M. (2021) · PeerJ · doi:10.7717/peerj.10893 · Cited by 18 · see citing works
Reali, P., Lolatto, R., Coelli, S., Tartaglia, G., & Bianchi, A. M. (2022) · Sensors · doi:10.3390/s22041428 · Cited by 18 · see citing works
Wu, Z., Li, X., Feng, Z., Wan, C., Ya, L., Li, T., Yang, Q., Liu, X., Ren, M., Li, J., et al. (2023) · Advanced Healthcare Materials · doi:10.1002/adhm.202202629 · Cited by 19 · see citing works
Buddhika, T., Zhang, H., Chan, S., Dissanayake, V., Nanayakkara, S. C., & Zimmermann, R. (2019) · Augmented Human International Conference · doi:10.1145/3311823.3311839 · Cited by 18 · see citing works
Sinichi, M., Gevonden, M. J., & Krabbendam, L. (2025) · Psychophysiology · doi:10.1111/psyp.70004 · Cited by 22 · see citing works
Lin, Z., Zhang, J., Chen, Y., & Zhang, Q. (2015) · International Conference on Communications · doi:10.1109/icc.2015.7248369 · Cited by 17 · see citing works
Examining the Role of Implicit Emotional Judgments in Social Anxiety and Experiential Avoidance
Levin, M. E., Haeger, J., & Smith, G. S. (2017) · Journal of Psychopathology and Behavioral Assessment · doi:10.1007/s10862-016-9583-5 · Cited by 16 · see citing works
Yan, J., Ye, Z., Shi, F., Dai, Y., Yang, L., Wu, J., & Wang, Y. (2021) · Biomedical Optics Express · doi:10.1364/boe.437805 · Cited by 16 · see citing works
Giovanni, E. D., Srinivasan Murali, A., Rincón, F. J., & Atienza, D. (2016) · Euromicro Conference on Digital System Design (DSD) · doi:10.1109/dsd.2016.101 · Cited by 15 · see citing works
Motion Artifact Detection in PPG Signals Based on Gramian Angular Field and 2-D-CNN
Liu, X., Hu, Q., Yuan, H., & Yang, C. (2020) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei51763.2020.9263630 · Cited by 15 · see citing works
Hayirlioglu, Y. Z., & Semiz, B. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2024.3403846 · Cited by 13 · see citing works
Hsiao, C.-C., Horng, J., Lee, R.-G., & Lin, R. (2017) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2017.8123084 · Cited by 13 · see citing works
van Es, V. V., de Lathauwer, I. D., Kemps, H., Handjaras, G., & Betta, M. (2024) · Bioengineering · doi:10.3390/bioengineering11101045 · Cited by 12 · see citing works
Ceugniez, M., Devanne, H., & Hermand, É. (2024) · JMIR mhealth and uhealth · doi:10.2196/54871 · Cited by 11 · see citing works
Measurement of Blood Pressure via a Skin-Mounted, Non-Invasive Pressure Sensor
Li, S., Park, Y., Luan, H., Wang, H., Kwon, K., Rogers, J. A., & Huang, Y. Y. (2021) · Journal of Applied Mechanics · doi:10.1115/1.4051183 · Cited by 12 · see citing works
mWIoTAuth: Multi-wearable data-driven implicit IoT authentication
Vhaduri, S., Dibbo, S. V., Muratyan, A., & Cheung, W. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.05.025 · Cited by 12 · see citing works
Non-invasive measurement of pulse waves in the soles of rats using an RGB camera
Takahashi, M., Yamaguchi, T., Takahashi, R., Ogawa‐Ochiai, K., Tsumura, N., & Iijima, N. (2021) · OSA Continuum · doi:10.1364/osac.433228 · Cited by 11 · see citing works
Wearable Upper Arm SpO 2 Sensor for Wellness Monitoring
Kinnunen, M. T., Behfar, M. H., Santaniemi, N., Happonen, T., Nguyen, D. H. P., Kilpijärvi, J., Jaako, T., Happonen, J., Russell, M. K., Clermont, C. A., et al. (2024) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2024.3521189 · Cited by 10 · see citing works
Novel Continuous Respiratory Rate Monitoring Using an Armband Wearable Sensor
Huang, N., Zhou, M., Bian, D., Mehta, P., Shah, M., Rajput, K. S., & Selvaraj, N. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9630025 · Cited by 10 · see citing works
Abe, M., Yoshizawa, M., Obara, K., Sugita, N., Homma, N., & Yambe, T. (2015) · Advanced Biomedical Engineering · doi:10.14326/abe.4.1 · Cited by 10 · see citing works
Wearable photoplethysmography devices
Charlton, P. H., & Marozas, V. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823374-0.00011-6 · Cited by 10 · see citing works
Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors
Hibbing, P. R., & Khan, M. M. (2024) · JMIR mhealth and uhealth · doi:10.2196/57158 · Cited by 10 · see citing works
Li, D., Xu, Y., & Gao, W. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.105156 · Cited by 9 · see citing works
Bubb, C. A. B., Weber, M., Kretsch, N., Heim, R. R., Zellhuber, I., Schmid, S., Kagerbauer, S. M., Kreuzer, J., Schaller, S. J., Blobner, M., et al. (2023) · Digital Health · doi:10.1177/20552076231211169 · Cited by 9 · see citing works
- Authors
- Maeda, Y., Sekine, M., & Tamura, T.
- Affiliations
- Chiba University (JP)
- Corresponding author
- Maeda, Yuka
- Venue
- Journal of Medical Systems
- Published
- 2010-05-07
- Volume
- 35
- Issue
- 5
- Pages
- 969-976
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- OpenAlex
- W1974364930
- Cited by
- 203
- References
- 12
- Citations by year
- 2026: 17 · 2025: 23 · 2024: 24 · 2023: 20 · 2022: 22 · 2021: 24 · 2020: 24 · 2019: 11 · 2018: 8 · 2017: 5 · 2016: 6 · 2015: 8 · 2014: 6 · 2013: 3 · 2012: 1
- FWCI
- 0.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Medical Systems (publishedVersion)
- PubMed (publishedVersion)
- 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 › Complementary and alternative medicine › Cardiovascular and exercise physiology
- Keywords
- photoplethysmography, motion artifacts, wearable sensors, pulse rate monitoring, upper arm, exercise monitoring
- MeSH terms
- Adult, Heart Rate, Humans, Infrared Rays, Light, Male, Movement, Signal Processing, Computer-Assisted, Photoplethysmography, Upper Extremity, Young Adult
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
