ArticleSensors (Basel, Switzerland)2022
Adaptive Motion Artifact Reduction in Wearable ECG Measurements Using Impedance Pneumography Signal.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed.
- From wrist to heart: clinical validation and real-world translation of wearable and portable AI-enhanced electrocardiography.European heart journal. Digital health · 2026Review
- Self-Maintaining Electrode-Skin Interface for Motion-Robust Biosignal Monitoring.Advanced healthcare materials · 2026Article
- High-Reliability Signal Quality Validation for Biosignals Using Sensor Fusion and Software Indices.Sensors (Basel, Switzerland) · 2026Article
- Human bioimpedance-based state detection technologies for sports health monitoring: a review.Frontiers in physiology · 2026Review
- Lightweight Deep Learning Architecture for Multi-Lead ECG Arrhythmia Detection.Sensors (Basel, Switzerland) · 2025Article
- ECG-Based Stress Detection and Productivity Factors Monitoring: The Real-Time Production Factory System.Sensors (Basel, Switzerland) · 2023Article
- ECG-Based Semi-Supervised Anomaly Detection for Early Detection and Monitoring of Epileptic Seizures.International journal of environmental research and public health · 2023Article
- Reduction in the Motion Artifacts in Noncontact ECG Measurements Using a Novel Designed Electrode Structure.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Noise is a common problem in wearable electrocardiogram (ECG) monitoring systems because the presence of noise can corrupt the ECG waveform causing inaccurate signal interpretation. By comparison with electromagnetic interference and its minimization, the reduction of motion artifact is more difficult and challenging because its time-frequency characteristics are unpredictable. Based on the characteristics of motion artifacts, this work uses adaptive filtering, a specially designed ECG device, and an Impedance Pneumography (IP) data acquisition system to combat motion artifacts. The newly designed ECG-IP acquisition system maximizes signal correlation by measuring both ECG and IP signals simultaneously using the same pair of electrodes. Signal comparison investigations between ECG and IP signals under five different body motions were carried out, and the Pearson Correlation Coefficient |r| was higher than 0.6 in all cases, indicating a good correlation. To optimize the performance of adaptive motion artifact reduction, the IP signal was filtered to a 5 Hz low-pass filter and then fed into a Recursive Least Squares (RLS) adaptive filter as a reference input signal. The performance of the proposed motion artifact reduction method was evaluated subjectively and objectively, and the results proved that the method could suppress the motion artifacts and achieve minimal distortion to the denoised ECG signal.
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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.