PPG derived heart rate estimation during intensive physical exercise

Motin, Mohammod Abdul, Karmakar, Chandan Kumar and Palaniswami, Marimuthu 2019, PPG derived heart rate estimation during intensive physical exercise, IEEE access, vol. 7, pp. 56062-56069, doi: 10.1109/ACCESS.2019.2913148.

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Title PPG derived heart rate estimation during intensive physical exercise
Author(s) Motin, Mohammod AbdulORCID iD for Motin, Mohammod Abdul orcid.org/0000-0003-1618-3772
Karmakar, Chandan KumarORCID iD for Karmakar, Chandan Kumar orcid.org/0000-0003-1814-0856
Palaniswami, Marimuthu
Journal name IEEE access
Volume number 7
Start page 56062
End page 56069
Total pages 8
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Publication date 2019
ISSN 2169-3536
Keyword(s) Science & Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Computer Science
Fast Fourier transform
heart rate
motion artifacts
photoplethysmographic signal
recursive Wiener filtering
recursive spectral subtraction
Summary Accurate and reliable estimation of heart rate (HR) from photoplethysmographic (PPG) signals during moderate and vigorous physical activities is a challenging task, since intense motion artifacts can easily disguise the true HR. A novel method for estimating HR from PPG signal, during intensive physical exercise, is presented in this paper. The proposed method employs a recursive Wiener filtering technique for HR estimation from motion artifacts-corrupted PPG signal and simultaneously recorded the triaxial accelerometer signal. The experimental results demonstrated that the average relative error and the average absolute error of the proposed method on a public dataset (IEEE 2015 Signal Processing Cup Database) of 23 PPG recordings were 1.73 and 1.85 beats per minute, respectively. Our proposed approach is faster and more accurate than the existing proposals. Therefore, the proposed algorithm can be a reliable solution for HR estimation from noisy PPG signal.
Language eng
DOI 10.1109/ACCESS.2019.2913148
HERDC Research category C1 Refereed article in a scholarly journal
Grant ID DP190101248
Copyright notice ©2019, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30122337

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