DocumentCode
3603801
Title
Motion Noise Cancelation in Heartbeat Sensing using Accelerometer and Adaptive Filter
Author
Ardalan, Shahab ; Moghadami, Siavash ; Jaafari, Samira
Author_Institution
Dept. of Electr. Eng., San Jose State Univ., San Jose, CA, USA
Volume
7
Issue
4
fYear
2015
Firstpage
101
Lastpage
104
Abstract
This letter focuses on suppressing the motion artifact of wrist photoplethysmographic heart rate signals using an accelerometer based adaptive filter. Monitoring of the heart signal can offer important insights with regard to health and wellness. The objective of the experiment conducted here is to recover the distorted signal resulting from body movement while measuring the heart rate signal noninvasively from the wrist. The class of filters, known as adaptive filters, that can extract meaningful information from the distorted signal, used predetermined initial conditions to equalize the signal distortion due to motion. Adaptive filters of least mean-square (LMS), Kalman filter, and recursive least-squares (RLS) were used in this study to recover the distorted heart rate signal. This study also presented a comparison on utilized filters that can be used for recovering of the heart rate signal.
Keywords
accelerometers; adaptive Kalman filters; cardiology; feature extraction; least mean squares methods; medical signal processing; photoplethysmography; recursive estimation; Kalman filter; LMS; RLS; accelerometer; adaptive filter; heartbeat sensing; information extraction; least mean-square; motion noise cancelation; recursive least-squares; wrist photoplethysmographic heart rate signals; Adaptive filters; Body sensor networks; Heart rate; Kalman filters; Least squares approximations; Photoplethysmography; Wearable computers; Body sensors; health; heart rate signal; photoplethysmography; vital signs; wearable;
fLanguage
English
Journal_Title
Embedded Systems Letters, IEEE
Publisher
ieee
ISSN
1943-0663
Type
jour
DOI
10.1109/LES.2015.2457933
Filename
7161281
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