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 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.