An Efficient Motion-Resistant Method for Wearable Pulse Oximeter
Abstract
Reduction of motion artifact and power saving are crucial in designing a wearable pulse oximeter for long-term telemedicine application. In this paper, a novel algorithm, minimum correlation discrete saturation transform (MCDST) has been developed for the estimation of arterial oxygen saturation (SaO2), based on an optical model derived from photon diffusion analysis. The simulation shows that the new algorithm MCDST is more robust under low SNRs than the clinically verified motion-resistant algorithm discrete saturation transform (DST). Further, the experiment with different severity of motions demonstrates that MCDST has a slightly better performance than DST algorithm. Moreover, MCDST is more computationally efficient than DST because the former uses linear algebra instead of the time-consuming adaptive filter used by latter, which indicates that MCDST can reduce the required power consumption and circuit complexity of the implementation. This is vital for wearable devices, where the physical size and long battery life are crucial.
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Although systems of this type have shown promising results, additional work appears necessary to achieve motion artifact reduction.
“Although systems of this type have shown promising results, additional work appears to be necessary to achieve motion artifact reduction [27,28].”
From A review of wearable sensors and systems with application in rehabilitation (2012) · cites this paper as [27]
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- Authors
- Yan, Y.-S., & Zhang, Y.-T.
- Affiliations
- Chinese University of Hong Kong (HK)
- Venue
- IEEE Transactions on Information Technology in Biomedicine
- Published
- 2008-05
- Volume
- 12
- Issue
- 3
- Pages
- 399-405
- ISSN
- 1089-7771 (ISSN-L)
- 1558-0032
- OpenAlex
- W2158319938
- Cited by
- 62
- References
- 17
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 3 · 2022: 4 · 2021: 3 · 2020: 3 · 2019: 1 · 2018: 2 · 2017: 5 · 2016: 8 · 2015: 4 · 2014: 4 · 2013: 3 · 2012: 5
- FWCI
- 3.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Information Technology in Biomedicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- motion artifact reduction, low signal-to-noise ratio, energy consumption reduction, telemedicine, computational efficiency
- MeSH terms
- Algorithms, Diagnosis, Computer-Assisted, Humans, Motion, Oximetry, Sensitivity and Specificity, Reproducibility of Results, Artifacts, Monitoring, Ambulatory
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