Photoplethysmography-based heart rate monitoring in physical activities via joint sparse spectrum reconstruction
Open accessAbstract
GOAL: A new method for heart rate monitoring using photoplethysmography (PPG) during physical activities is proposed. METHODS: It jointly estimates the spectra of PPG signals and simultaneous acceleration signals, utilizing the multiple measurement vector model in sparse signal recovery. Due to a common sparsity constraint on spectral coefficients, the method can easily identify and remove the spectral peaks of motion artifact (MA) in the PPG spectra. Thus, it does not need any extra signal processing modular to remove MA as in some other algorithms. Furthermore, seeking spectral peaks associated with heart rate is simplified. RESULTS: Experimental results on 12 PPG datasets sampled at 25 Hz and recorded during subjects' fast running showed that it had high performance. The average absolute estimation error was 1.28 beat/min and the standard deviation was 2.61 beat/min. CONCLUSION AND SIGNIFICANCE: These results show that the method has great potential to be used for PPG-based heart rate monitoring in wearable devices for fitness tracking and health monitoring.
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Secondary sensors can be integrated into PPG sensors to detect motion, including accelerometers, gyroscopes, piezoelectric transducers, or another wavelength of light as a motion reference.
“As implemented by consumer-grade HR monitors, secondary sensors can also be integrated into PPG sensors to detect motion. These include accelerometers [175,176,177,178,179], gyroscopes [179,180], piezoelectric transducers [181], or the utilization of another wavelength of light as a motion reference [182,183].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [178]
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- Authors
- Zhang, Z.
- Corresponding author
- Zhang, Zhilin
- ORCID
- Zhang, Zhilin
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2015-08
- Volume
- 62
- Issue
- 8
- Pages
- 1902-1910
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2151713296
- Cited by
- 388
- References
- 24
- Citations by year
- 2026: 16 · 2025: 28 · 2024: 22 · 2023: 38 · 2022: 32 · 2021: 37 · 2020: 40 · 2019: 52 · 2018: 37 · 2017: 41 · 2016: 36 · 2015: 9
- FWCI
- 20.38
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Samsung Research America–Dallas
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- photoplethysmography, heart rate monitoring, motion artifact removal, wearable devices, fitness tracking, physical activity
- MeSH terms
- Adolescent, Adult, Algorithms, Clothing, Heart Rate, Humans, Male, Monitoring, Physiologic, Pulse, Signal Processing, Computer-Assisted, Photoplethysmography, Young Adult
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