A Chest Strap-Based System for Electrocardiogram Monitoring

To address the issues of poor comfort and limited mobility associated with traditional ECG monitoring systems, this study developed a chest strap ECG monitoring system (CEMS) utilizing silver-coated polyamide yarn. This system can continuously capture high-quality ECG signals during daily activities...

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Bibliographic Details
Main Authors: Xiaoman Zhang, Yaoliang Zhan, Xue Wang, Jin Yang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/11/5920
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Summary:To address the issues of poor comfort and limited mobility associated with traditional ECG monitoring systems, this study developed a chest strap ECG monitoring system (CEMS) utilizing silver-coated polyamide yarn. This system can continuously capture high-quality ECG signals during daily activities such as walking and running, without restricting the user’s movement. Real-time data display and storage are enabled through a built-in Bluetooth module. Furthermore, leveraging these high-quality ECG signals, a classification model based on a fully connected neural network was constructed to evaluate exercise intensity by analyzing key ECG features. After 100 training epochs, the model achieved a classification accuracy of 98.7% for running intensity. The integration of this model with the CEMS enables effective tracking of ECG signals and accurate assessment of exercise intensity, offering a promising and practical solution for next-generation wearable signal monitoring systems.
ISSN:2076-3417