Removing movement artifacts from equine ECG recordings acquired with textile electrodes

Area of Science:

• Veterinary Medicine
• Biomedical Engineering
• Signal Processing

Background:

• Movement artifacts (MA) significantly degrade electrocardiogram (ECG) recordings in freely moving animals.
• Accurate ECG analysis is crucial for equine health monitoring.
• Existing methods struggle with artifact reduction in dynamic conditions.

Purpose of the Study:

• To develop and implement a novel wearable system for detecting and reducing MA in equine ECG.
• To introduce a new algorithm utilizing Stationary Wavelet Transform (SWT) for MA removal.
• To assess the effectiveness of the system and algorithm in real-world conditions.

Main Methods:

• A wearable system integrating textile electrodes for ECG and a triaxial accelerometer for movement monitoring was developed.
• ECG and physical activity data were continuously acquired from seven horses.
• A new algorithm employing Stationary Wavelet Transform (SWT) decomposition was implemented for MA identification and removal.

Main Results:

• The system successfully acquired simultaneous ECG and movement data from horses.
• The proposed SWT-based algorithm demonstrated significant MA reduction.
• A reduction in MA percentage exceeding 40% was achieved across seven hours of recordings.

Conclusions:

• The novel wearable system and SWT algorithm effectively reduce movement artifacts in equine ECG.
• This technology enhances the quality of ECG data for horses in motion.
• The findings support improved non-invasive cardiovascular monitoring in equine research and practice.