Motion Artifact Reduction for Wrist-Worn Photoplethysmograph Sensors Based on Different Wavelengths
Open accessAbstract
Long-term heart rate (HR) monitoring by wrist-worn photoplethysmograph (PPG) sensors enables the assessment of health conditions during daily life with high user comfort. However, PPG signals are vulnerable to motion artifacts (MAs), which significantly affect the accuracy of estimated physiological parameters such as HR. This paper proposes a novel modular algorithm framework for MA removal based on different wavelengths for wrist-worn PPG sensors. The framework uses a green PPG signal for HR monitoring and an infrared PPG signal as the motion reference. The proposed framework includes four main steps: motion detection, motion removal using continuous wavelet transform, approximate HR estimation and signal reconstruction. The proposed algorithm is evaluated against an electrocardiogram (ECG) in terms of HR error for a dataset of 6 healthy subjects performing 21 types of motion. The proposed MA removal method reduced the average error in HR estimation from 4.3, 3.0 and 3.8 bpm to 0.6, 1.0 and 2.1 bpm in periodic, random, and continuous non-periodic motion situations, respectively.
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Motion artifacts may manifest as missing or false beats, which result in incorrect heart rate calculations.
“Motion artifacts may manifest as missing or false beats which result in incorrect HR calculations.”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [35]
The Introduction says motion artifacts distort wrist-worn PPG signals, and Section 5.2 reports HR-estimation errors that are reduced by artifact removal. Section 4.5 discusses beat-to-beat HR detection, but the passages do not identify missing or false beats as the way motion artifacts cause those errors. Page numbers are not available in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measuredWearable devices have higher error during activity than at rest.
“Our analyses reinforces the growing body of research demonstrating that wearable devices have higher error during activity than at rest.8,11,35,38,39”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [35]
The Introduction says motion can distort wrist-worn PPG signals, and Section 4.1 reports a higher peak-to-noise ratio in stationary conditions than in several motion conditions. These passages support the direction of the claim for wrist-worn PPG, but the paper does not establish that wearable devices generally have higher measurement error during activity than at rest. (LLM, conf=0.78)
Experimental — accuracy not yet measuredHeart rate measurements from wearable devices are often less accurate during physical activity or cyclic wrist motions.
“Several studies have demonstrated that HR measurements from wearable devices are often less accurate during physical activity or cyclic wrist motions.”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [35]
Motion artefact is a suspected error with wrist-worn sensors, particularly during long-term heart rate monitoring.
“Motion artefact is a suspected error with wrist-worn sensors, particularly during long-term heart rate monitoring [97].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [97]
Both the piezoelectric transducer and another wavelength of light can pick up finer motions such as finger tapping.
“Both the piezoelectric transducer and another wavelength of light can pick up these finer motions [181,182].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [182]
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References 24 · Cited by 140
- Authors
- Zhang, Y., Song, S., Vullings, R., Biswas, D., Simões-Capela, N., van Helleputte, N., van Hoof, C., & Groenendaal, W.
- Affiliations
- Holst Centre (Netherlands) (NL)
- IMEC (BE)
- Eindhoven University of Technology (NL)
- imec vzw, 3001 Leuven, Belgium
- Corresponding author
- Song, Shuang
- Groenendaal, Willemijn
- ORCID
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2019-02-07
- Volume
- 19
- Issue
- 3
- Pages
- 673
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC6387309
- OpenAlex
- W2912732526
- Cited by
- 140
- References
- 24
- Citations by year
- 2026: 16 · 2025: 16 · 2024: 18 · 2023: 14 · 2022: 21 · 2021: 33 · 2020: 19 · 2019: 3
- FWCI
- 6.69
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- TU/e Research Portal (publishedVersion, other-oa)
- Lirias (submittedVersion, other-oa)
- TU/e Research Portal (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- TU/e Research Portal (submittedVersion, other-oa)
- 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
- motion artifact reduction, photoplethysmography, wrist-worn sensors, heart rate monitoring, motion detection, continuous wavelet transform, heart rate estimation, signal reconstruction, long-term physiological monitoring
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