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Related Experiment Video

Updated: Jun 13, 2026

Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment

Conformable Wearable Electrodes: From Fabrication to Electrophysiological Assessment

Published on: July 22, 2022

Design and performance evaluation of a dynamic wearable ECG system based on the MC-DST method.

Yu Zheng^1,2, Ao Han², Dongying Wang³

¹School of Life Sciences, Tiangong University, Tianjin, China.

Computer Methods in Biomechanics and Biomedical Engineering

|June 11, 2026

Summary

This study introduces a wearable electrocardiogram (ECG) system with low-impedance silver fiber electrodes for accurate, 24-hour heart monitoring. It effectively suppresses motion artifacts using a novel algorithm, ensuring high R-peak detection accuracy.

Keywords:

MC-DST R-peak detection Wearable ECG monitoring flexible fabric electrode motion artifact suppression

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Area of Science:

Biomedical Engineering
Wearable Technology
Cardiovascular Monitoring

Background:

Continuous electrocardiogram (ECG) monitoring is crucial for diagnosing cardiac conditions.
Existing wearable systems often struggle with motion artifacts and electrode contact impedance.
Improving R-peak detection accuracy and signal quality in dynamic environments is essential.

Purpose of the Study:

To develop a wearable ECG monitoring system with high-fidelity signal acquisition.
To implement an advanced algorithm for artifact suppression and R-peak detection.
To validate the system's performance in real-world dynamic monitoring scenarios.

Main Methods:

Utilized silver fiber fabric electrodes with contact impedance < 10 Ω.
Employed STM32F411RCT6 and ADS1292 chips for data acquisition and processing.
Developed a hybrid Morphological Contour-Dual Slope Threshold (MC-DST) algorithm for signal analysis.
Integrated Bluetooth 5.0 and a 64 GB SD card for continuous data logging.

Main Results:

Achieved 24-hour continuous operation with low power consumption.
The MC-DST algorithm effectively eliminated baseline drift and suppressed motion artifacts.
Demonstrated high R-peak detection accuracy of 99.38%.
Achieved a sensitivity of 99.52% in dynamic monitoring tests.

Conclusions:

The developed wearable ECG system provides reliable, long-term cardiac monitoring.
The novel MC-DST algorithm significantly enhances signal quality and detection accuracy.
The system shows great potential for clinical applications and remote patient monitoring.