The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Motion-Tolerant Adaptive Algorithm for Wearable Photoplethysmographic Biosensors
Abstract
The performance of portable and wearable biosensors is highly influenced by motion artifact. In this paper, a novel real-time adaptive algorithm is proposed for accurate motion-tolerant extraction of heart rate (HR) and pulse oximeter oxygen saturation ( SpO2) from wearable photoplethysmographic (PPG) biosensors. The proposed algorithm removes motion artifact due to various sources including tissue effect and venous blood changes during body movements and provides noise-free PPG waveforms for further feature extraction. A two-stage normalized least mean square adaptive noise canceler is designed and validated using a novel synthetic reference signal at each stage. Evaluation of the proposed algorithm is done by Bland-Altman agreement and correlation analyses against reference HR from commercial ECG and SpO2 sensors during standing, walking, and running at different conditions for a single- and multisubject scenarios. Experimental results indicate high agreement and high correlation (more than 0.98 for HR and 0.7 for SpO2 extraction) between measurements by reference sensors and our algorithm.
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Citations
Cites
Respiratory sinus arrhythmia in humans: how breathing pattern modulates heart rate
Hirsch, J. A., & Bishop, B. (1981) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.1981.241.4.h620 · Cited by 1,105
Mobile monitoring with wearable photoplethysmographic biosensors
Asada, H. H., Shaltis, P., Reisner, A., Rhee, S., & Hutchinson, R. C. (2003) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2003.1213624 · Cited by 466
Cited by
Wearable and flexible electronics for continuous molecular monitoring
Yang, Y., & Gao, W. (2019) · Chemical Society Reviews · doi:10.1039/c7cs00730b · Cited by 1,315
Wearable photoplethysmographic sensors—past and present
Tamura, T., Maeda, Y., Sekine, M., & Yoshida, M. (2014) · Electronics · doi:10.3390/electronics3020282 · Cited by 912
Emerging Technologies of Flexible Pressure Sensors: Materials, Modeling, Devices, and Manufacturing
Huang, Y., Fan, X., Chen, S., & Zhao, N. (2019) · Advanced Functional Materials · doi:10.1002/adfm.201808509 · Cited by 543
Zhang, Z. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2406332 · Cited by 388
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
Metadata
- Authors
- Yousefi, R., Nourani, M., Ostadabbas, S., & Panahi, I.
- Venue
- IEEE Journal of Biomedical and Health Informatics
- Published
- 2014-03
- Volume
- 18
- Issue
- 2
- Pages
- 670-681
- ISSN
- 2168-2194 (ISSN-L)
- 2168-2208
- OpenAlex
- W2030134993
- Cited by
- 228
- References
- 2
- FWCI
- 10.63
- Type
- journal article
- Language
- en
- Open access
- closed
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- Yousefi, R., Nourani, M., Ostadabbas, S., & Panahi, I. (2014). A Motion-Tolerant Adaptive Algorithm for Wearable Photoplethysmographic Biosensors. IEEE Journal of Biomedical and Health Informatics. https://doi.org/10.1109/jbhi.2013.2264358
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