Improving Signal Quality in Non-Contact Electrocardiography: Novel Strategy for Motion Artifact Reduction

Area of Science:

• Biomedical Engineering
• Signal Processing
• Wearable Technology

Background:

• Capacitive electrocardiography (cECG) offers non-contact heart rate monitoring but is severely limited by motion artifacts.
• Existing methods struggle to effectively remove motion-induced noise while preserving signal integrity.

Purpose of the Study:

• To develop and validate a novel method for motion artifact removal in cECG using non-contact floating electrodes and adaptive filtering.
• To enhance the reliability and practical applicability of cECG for continuous heart rate monitoring.

Main Methods:

• Utilized non-contact floating electrodes to capture ambient 50 Hz mains interference, modulated by motion.
• Employed multi-reference Normalized Least Mean Squares (NLMS) adaptive filtering with six derived reference signals.
• Integrated a hysteresis-based motion detector for selective artifact removal during motion periods.

Main Results:

• Demonstrated consistent improvement in R-peak detection accuracy during induced motion periods.
• Achieved substantial reduction in artifact energy (RMS) in motion regions.
• Validated the method's effectiveness across multiple subjects, sessions, and environments.

Conclusions:

• The proposed reference-electrode architecture and adaptive filtering effectively suppress motion artifacts in cECG.
• This approach significantly enhances the robustness of non-contact ECG monitoring, paving the way for practical applications.
• The method shows promise for artifact removal irrespective of the motion's physical origin.