ArticleSensors (Basel, Switzerland)2019
Motion Artifact Reduction for Wrist-Worn Photoplethysmograph Sensors Based on Different Wavelengths.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network.British journal of sports medicine · 2021Guideline
- Laser-Induced Graphene Electrodes for Wrist-Worn Impedance Plethysmography Measurements: A Feasibility Study.Biosensors · 2026Article
- From Sensing to Sense-Making: A Framework for On-Person Intelligence with Wearable Biosensors and Edge LLMs.Sensors (Basel, Switzerland) · 2026Article
- A Pilot Study Examining the Convergent Validity of Two Commercially Available Heart Rate Monitoring Devices During Swimming of Different Intensities and Strokes.International journal of exercise science · 2026Article
- Mathematical modeling of heart rate tracking in motion affected PPG signals.Scientific reports · 2025Article
- A novel approach to exercise heart rate estimation combining PPG quality assessment with DNN modeling.Medical & biological engineering & computing · 2025Article
- Continuous biosignal acquisition beyond the limit of epidermal turnover.Materials horizons · 2025Review
- Accuracy of Heart Rate Measurement Under Transient States: A Validation Study of Wearables for Real-Life Monitoring.Sensors (Basel, Switzerland) · 2025Article
- Polarity-tunable dye-sensitized optoelectronic artificial synapses for physical reservoir computing-based machine vision.Scientific reports · 2025Article
- Machine Learning-Based VOBiosensors · 2025Article
- Wrist-Worn and Arm-Worn Wearables for Monitoring Heart Rate During Sedentary and Light-to-Vigorous Physical Activities: Device Validation Study.JMIR cardio · 2025Article
- Quality in Question: Assessing the Accuracy of Four Heart Rate Wearables and the Implications for Psychophysiological Research.Psychophysiology · 2025Article
- Machine Learning Applied to Reference Signal-Less Detection of Motion Artifacts in Photoplethysmographic Signals: A Review.Sensors (Basel, Switzerland) · 2024Review
- Association Between Cognitive Function and the Autonomic Nervous System by Photoplethysmography.Bioengineering (Basel, Switzerland) · 2024Article
- Imaging of the vascular distribution of the outer ear using optical coherence tomography angiography for highly accurate positioning of a hearable sensor.APL bioengineering · 2024Article
- Remote Short Sessions of Heart Rate Variability Biofeedback Monitored With Wearable Technology: Open-Label Prospective Feasibility Study.JMIR mental health · 2024Article
- A Novel Signal Restoration Method of Noisy Photoplethysmograms for Uninterrupted Health Monitoring.Sensors (Basel, Switzerland) · 2023Article
- The 2023 wearable photoplethysmography roadmap.Physiological measurement · 2023Review
- Anomaly Detection in Multi-Wavelength Photoplethysmography Using Lightweight Machine Learning Algorithms.Sensors (Basel, Switzerland) · 2023Article
- An ML-Based Approach to Reconstruct Heart Rate from PPG in Presence of Motion Artifacts.Biosensors · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.