Nowadays, the large-scale deployment of electronic health record systems and eHealth services has to face with a real multi-vendor environment. Even if each manufacturer supports an existing standard for communication and storage of ECG data, the la
ECG (electrocardiogram) data classification has a great variety of applications in health monitoring and diagnosis facilitation. In this paper, previous work on automatic ECG data classification is overviewed, the idea of applying deep learning tool
—A wearable ECG monitoring device with a customized SoC is proposed. The ECG signal sensed with passive electrodes is amplified, digitized and transformed into wavelet coefficients by this dedicated SoC. Following with it, a low power microcontrolle
