Non-Contact Monitoring of ECG in the Home Environment-Selecting Optimal Electrode Configuration

Area of Science:

• Biomedical Engineering
• Cardiovascular Monitoring
• Signal Processing

Background:

• Capacitive electrocardiography (cECG) is frequently integrated into wearable and embedded systems for physiological monitoring.
• Traditional ECG lead placement can be suboptimal for embedded systems, particularly concerning motion artifacts and signal quality.
• Identifying optimal lead configurations is crucial for maximizing signal fidelity in cECG applications.

Purpose of the Study:

• To determine an optimal electrocardiographic lead configuration for embedded cECG systems.
• To define optimal lead placement based on maximizing R-wave amplitude and minimizing motion artifacts.
• To validate the proposed lead configuration through experimental studies.

Main Methods:

• Model studies were employed to define the optimal lead as the one yielding the highest R-wave amplitude on the subject's back.
• Analysis included minimizing susceptibility to motion artifacts by considering electrode placement areas with high voltage and low potential gradients.
• An experimental system was developed and tested on 14 participants, comparing optimal back leads with chest leads.

Main Results:

• The optimal lead direction was found to align with the electrical axis of the heart.
• Experimental results showed an R-wave amplitude ratio (back/chest) less than 1, with a signal-to-noise ratio (SNR) of at least 20 dB.
• High-quality QRS complex detection was achieved with a positive predictive value (PPV) of 97% using optimal leads, while suboptimal configurations yielded uninterpretable signals.

Conclusions:

• Individualized optimal lead placement, particularly on the back, can significantly enhance cECG signal quality for embedded systems.
• The identified optimal lead configuration, aligned with the heart's electrical axis, effectively maximizes R-wave amplitude and minimizes motion artifacts.
• This approach enables reliable QRS complex detection, crucial for accurate cardiac monitoring in non-traditional cECG implementations.