A Robust and Customizable Tracking Algorithm for Accurate Heart Rate Estimation (demo)
Pages 665 - 666
Abstract
Wearable health monitoring has become a very familiar term in today'sworld. One of the most popular means ofwearable sensing is photoplethysmogram (PPG). Due to its unobtrusive and ubiquitous nature, it is gaining popularity among people everywhere. Due to the ease of use, the utility of such technology is increasing day by day. However, in theworld of researchers, the accurate estimation of heart rate (HR) in presence of motion artefacts remains an unsolved problem due to the susceptibility of PPG signals to corruption by motion artefacts. The way in which a person fastens the device on the wrist plays an important role in the acquisition of signal from the device. While there are various research works going on in this field, there is always a trade-off between accuracy and complexity of algorithm and hardware resources. Also, in such scenarios where the sensor gets misplaced due to movements, there might be no PPG signal component available in the acquired signal data. In such cases the sophisticated denoising algorithms make no sense.
References
[1]
Zhang et al.,"TROIKA : A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise", IEEE Trans. on Biomedical Engineering, vol. 62, no. 2, pp. 522--531, February 2015.
[2]
.Sun et al., "A new approach for heart rate monitoring using photoplethysmography signals contaminated by motion artifacts," 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, 2016, pp. 809--813.
[3]
akynthinaki MS (2015) "Modelling Heart Rate Kinetics". PLoS ONE 10(4): e0118263.
[4]
.Mukhopadhyay et al.,"A Photoplethysmograph Based Practical Heart Rate Estimation Algorithm for Wearable Platforms". 2017 Workshop on Wearable Systems and Applications (WearSys '17). ACM, New York, NY, USA, 23--28.
[5]
asimuddin Ahmed et al, "Heart Rate Estimation Algorithm From Wrist-based Photoplethysmogram Using Subspace Learning Method", 2019 WristSense, IEEE PerCom, Inpress
Index Terms
- A Robust and Customizable Tracking Algorithm for Accurate Heart Rate Estimation (demo)
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Information
Published In
June 2019
736 pages
ISBN:9781450366618
DOI:10.1145/3307334
- General Chairs:
- Junehwa Song,
- Minkyong Kim,
- Program Chairs:
- Nicholas D. Lane,
- Rajesh K. Balan
Copyright © 2019 Owner/Author.
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Association for Computing Machinery
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Published: 12 June 2019
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MobiSys '19
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MobiSys '19: The 17th Annual International Conference on Mobile Systems, Applications, and Services
June 17 - 21, 2019
Seoul, Republic of Korea
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