A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device

This paper presents a novel approach, adaptive spectrum noise cancellation (ASNC), for motion artifacts removal in photoplethysmography (PPG) signals measured by an optical biosensor to obtain clean PPG waveforms for heartbeat rate calculation. One challenge faced by this optical sensing method is t...

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Main Authors: Dong Yang, Yongqiang Cheng, Jin Zhu, Dongfei Xue, Grant Abt, Hangyang Ye, Yonghong Peng
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8302487/
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author Dong Yang
Yongqiang Cheng
Jin Zhu
Dongfei Xue
Grant Abt
Hangyang Ye
Yonghong Peng
author_facet Dong Yang
Yongqiang Cheng
Jin Zhu
Dongfei Xue
Grant Abt
Hangyang Ye
Yonghong Peng
author_sort Dong Yang
collection DOAJ
description This paper presents a novel approach, adaptive spectrum noise cancellation (ASNC), for motion artifacts removal in photoplethysmography (PPG) signals measured by an optical biosensor to obtain clean PPG waveforms for heartbeat rate calculation. One challenge faced by this optical sensing method is the inevitable noise induced by movement when the user is in motion, especially when the motion frequency is very close to the target heartbeat rate. The proposed ASNC utilizes the onboard accelerometer and gyroscope sensors to detect and remove the artifacts adaptively, thus obtaining accurate heartbeat rate measurement while in motion. The ASNC algorithm makes use of a commonly accepted spectrum analysis approaches in medical digital signal processing, discrete cosine transform, to carry out frequency domain analysis. Results obtained by the proposed ASNC have been compared with the classic algorithms, the adaptive threshold peak detection and adaptive noise cancellation. The mean (standard deviation) absolute error and mean relative error of heartbeat rate calculated by ASNC is 0.33 (0.57) beats min<sup>-1</sup> and 0.65%, by adaptive threshold peak detection algorithm is 2.29 (2.21) beats min<sup>-1</sup> and 8.38%, by adaptive noise cancellation algorithm is 1.70 (1.50) beats min<sup>-1</sup> and 2.02%. While all algorithms performed well with both simulated PPG data and clean PPG data collected from our verity device in situations free of motion artifacts, ASNC provided better accuracy when motion artifacts increase, especially when motion frequency is very close to the heartbeat rate.
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spelling doaj.art-60dc80145d2d47cd922f05a358c99e7d2022-12-21T20:18:38ZengIEEEIEEE Access2169-35362018-01-0168364837510.1109/ACCESS.2018.28052238302487A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable DeviceDong Yang0Yongqiang Cheng1https://orcid.org/0000-0001-7282-7638Jin Zhu2Dongfei Xue3https://orcid.org/0000-0002-7566-7331Grant Abt4Hangyang Ye5Yonghong Peng6Department of Control Science and Engineering, Tongji University, Shanghai, ChinaSchool of Engineering and Computer Science, University of Hull, Hull, U.K.Department of Control Science and Engineering, Tongji University, Shanghai, ChinaSchool of Engineering and Computer Science, University of Hull, Hull, U.K.School of Life Sciences, University of Hull, Hull, U.K.Department of Control Science and Engineering, Tongji University, Shanghai, ChinaFaculty of Computer Science, University of Sunderland, Sunderland, U.K.This paper presents a novel approach, adaptive spectrum noise cancellation (ASNC), for motion artifacts removal in photoplethysmography (PPG) signals measured by an optical biosensor to obtain clean PPG waveforms for heartbeat rate calculation. One challenge faced by this optical sensing method is the inevitable noise induced by movement when the user is in motion, especially when the motion frequency is very close to the target heartbeat rate. The proposed ASNC utilizes the onboard accelerometer and gyroscope sensors to detect and remove the artifacts adaptively, thus obtaining accurate heartbeat rate measurement while in motion. The ASNC algorithm makes use of a commonly accepted spectrum analysis approaches in medical digital signal processing, discrete cosine transform, to carry out frequency domain analysis. Results obtained by the proposed ASNC have been compared with the classic algorithms, the adaptive threshold peak detection and adaptive noise cancellation. The mean (standard deviation) absolute error and mean relative error of heartbeat rate calculated by ASNC is 0.33 (0.57) beats min<sup>-1</sup> and 0.65%, by adaptive threshold peak detection algorithm is 2.29 (2.21) beats min<sup>-1</sup> and 8.38%, by adaptive noise cancellation algorithm is 1.70 (1.50) beats min<sup>-1</sup> and 2.02%. While all algorithms performed well with both simulated PPG data and clean PPG data collected from our verity device in situations free of motion artifacts, ASNC provided better accuracy when motion artifacts increase, especially when motion frequency is very close to the heartbeat rate.https://ieeexplore.ieee.org/document/8302487/Adaptive spectrum noise cancellationheartbeat rate measurementwearable devicePPGmotion artifacts
spellingShingle Dong Yang
Yongqiang Cheng
Jin Zhu
Dongfei Xue
Grant Abt
Hangyang Ye
Yonghong Peng
A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device
IEEE Access
Adaptive spectrum noise cancellation
heartbeat rate measurement
wearable device
PPG
motion artifacts
title A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device
title_full A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device
title_fullStr A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device
title_full_unstemmed A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device
title_short A Novel Adaptive Spectrum Noise Cancellation Approach for Enhancing Heartbeat Rate Monitoring in a Wearable Device
title_sort novel adaptive spectrum noise cancellation approach for enhancing heartbeat rate monitoring in a wearable device
topic Adaptive spectrum noise cancellation
heartbeat rate measurement
wearable device
PPG
motion artifacts
url https://ieeexplore.ieee.org/document/8302487/
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