期刊
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
卷 226, 期 -, 页码 -出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.cmpb.2022.107126
关键词
Reflectance-type photoplethysmography (PPG); Instantaneous heart rate (HR); Adaptive motion artifact reference selection; Acceleration signal; Gyroscope signal
类别
资金
- Korea Health Technology R&D Project through the Korea Health Industry De-velopment Institute (KHIDI) - Ministry of Health & Welfare, Republic of Korea [HV22C0233]
- Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) - Ministry of Health & Welfare, Republic of Korea [HV22C0233]
- Korea Medical Device Development Fund - Korea government (the Ministry of Science and ICT
- Ministry of Trade, Industry and Energy
- Ministry of Health and Welfare
- and Ministry of Food and Drug Safety) [HV22C0233]
- Basic Science Research Program through National Research Foundation of Korea (NRF) - Ministry of Science, ICT & Future Planning [KMDF_PR_20200901_0095]
- Italian MIUR PON R&I 2014-2020 AIM project [NRF-2020R1A2C1014829]
- Italian MIUR PRIN 2017 [AIM1851228-2]
- [2017WZFTZP]
This study aims to find an appropriate motion artifact (MA) reference selection approach for MA cancelation in wrist-worn photo-plethysmography (PPG). An adaptive MA reference selection method was proposed and demonstrated to provide higher accuracy in HR estimation compared to other approaches across five state-of-the-art methods. This research highlights the importance of accurate MA references in improving the overall performance of HR estimation algorithms.
Background and objective: Recently, various algorithms have been introduced using wrist-worn photo-plethysmography (PPG) to provide high accuracy of instantaneous heart rate (HR) estimation, including during high-intensity exercise. Most studies focus on using acceleration and/or gyroscope signals for the motion artifact (MA) reference, which attenuates or cancels out noise from the MA-corrupted PPG signals. We aim to open and pave the path to find an appropriate MA reference selection for MA cancelation in PPG.Methods: We investigated how the acceleration and gyroscope reference signals correlate with the MAs of the distorted PPG signals and derived both mathematically and experimentally an adaptive MA reference selection approach. We applied our algorithm to five state-of-the-art (SOTA) methods for the performance evaluation. In addition, we compared the four MA reference selection approaches, i.e. with acceleration signal only, with gyroscope signal only, with both signals, and using our proposed adaptive selection.Results: When applied to 47 PPG recordings acquired during intensive physical exercise from two differ-ent datasets, our proposed adaptive MA reference selection method provided higher accuracy than the other MA selection approaches for all five SOTA methods.Conclusion: Our proposed adaptive MA reference selection approach can be used in other MA cancelation methods and reduces the HR estimation error.Significance: We believe that this study helps researchers to address acceleration and gyroscope signals as accurate MA references, which eventually improves the overall performance for estimating HRs through the various algorithms developed by research groups.(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
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