Development of real-time motion artifact reduction algorithm for a wearable photoplethysmography
Abstract
This paper presents a motion artifact reduction algorithm for a real-time, wireless and wearable photoplethysmography (PPG) device for measuring heart beats. A wearable finger band PPG device consists of a 3-axis accelerometer, infrared LED, photo diode, a microprocessor and wireless module. Sources of the motion artifacts were investigated from the hand motions, through computing the correlations between the three directional finger motions and distorted PPG signals. A two-dimensional active noise cancellation algorithm was applied to compensate the distorted signals by motions, using the directional accelerometer data. NLMS (Normalized Least Mean Square) adaptive filter (4th order) was employed in the algorithm. As a result, the signals' distortion rates were reduced from 52.34% to 3.53%, at frequencies between 1 and 2.5 Hz, which representing daily motions such walking and jogging. The wearable health monitoring device equipped with the motion artifact reduction algorithm can be integrated as a terminal in a so-called ubiquitous healthcare system, which provides a continuous health monitoring without interrupting a daily life.
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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 [177]
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Wearable photoplethysmographic sensors—past and present
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“In another study, a two-dimensional (2-D) active noise cancellation algorithm was applied to compensate for motion-distorted signals using directional accelerometer data [55]; a NLMS adaptive filter (fourth-order) was used in the algorithm, resulting in a reduction in signal distortion from 52.”
MethodSources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring
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Organic Multi-Channel Optoelectronic Sensors for Wearable Health Monitoring
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- Authors
- Han, H., Kim, M.-J., & Kim, J.
- Affiliations
- Korea Advanced Institute of Science and Technology (KR)
- Venue
- 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
- Publisher
- IEEE
- Published
- 2007-08
- Volume
- 2007
- Pages
- 1538-1541
- ISSN
- 1557-170X (ISSN-L)
- OpenAlex
- W2111481778
- Cited by
- 101
- References
- 10
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 3 · 2022: 5 · 2021: 7 · 2020: 9 · 2019: 12 · 2018: 9 · 2017: 11 · 2016: 6 · 2015: 8 · 2014: 7 · 2013: 3 · 2012: 3
- FWCI
- 8.42
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Conference proceedings (publishedVersion)
- PubMed (publishedVersion)
- 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, motion artifact reduction, wearable sensors, accelerometer, active noise control, real-time signal processing, heart rate monitoring, wireless health monitoring, ubiquitous healthcare, walking and jogging
- MeSH terms
- Algorithms, Diagnosis, Computer-Assisted, Heart Rate, Humans, Motion, Sensitivity and Specificity, Reproducibility of Results, Artifacts, Photoplethysmography, Monitoring, Ambulatory
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