Signal Quality Analysis for Long-Term ECG Monitoring Using a Health Patch in Cardiac Patients

Area of Science:

• Biomedical Engineering
• Cardiology
• Digital Health

Background:

• Cardiovascular diseases (CVD), including atrial fibrillation (AF), pose a significant global health challenge.
• Timely diagnosis of CVD is crucial for effective treatment and reducing healthcare burdens.
• Ambulatory electrocardiogram (ECG) monitoring patches offer a promising approach for continuous patient assessment.

Purpose of the Study:

• To evaluate the long-term signal quality of a novel single-lead ECG monitoring patch.
• To investigate potential signal quality degradation over a 5-day monitoring period.
• To assess the impact of daily variations and patient activity on ECG signal integrity for CVD and AF detection.

Main Methods:

• Analysis of ECG signal quality from six cardiac patients using a self-adhesive dry electrode ECG patch over five days.
• Quantification of signal quality metrics and assessment of daily variations.
• Correlation of signal quality with patient activity levels, particularly distinguishing between day and night recordings.

Main Results:

• The single-lead ECG patch demonstrated consistent signal quality over the 5-day monitoring period.
• While daily variations in ECG quality were observed, they were not statistically significant.
• Higher signal quality was recorded during nighttime monitoring, indicating a reduction in motion artifacts.

Conclusions:

• The studied ECG monitoring patch technology shows potential for reliable, long-term ambulatory cardiac monitoring.
• Findings support the use of such patches for improved cardiovascular disease diagnosis and atrial fibrillation detection in real-world settings.
• Understanding the influence of motion artifacts on signal quality can refine diagnostic algorithms for wearable ECG devices.