@inproceedings{55b2d3f28e184957adedf1f06e5e637c,
title = "A Study on ECG Monitoring Embedded Systems",
abstract = "The technical development of the wearable devices has introduced the easy and compact ECG monitoring em-bedded systems. For the commercial ECG monitoring systems, classification is one of the key performance metrics. This is because the classification identifies the abnormal ECG signal and consequently leads to the appropriate treatment. Since the computing capability is needed for the classification, the server-based or gateway-based classification is usually considered. This means that the embedded system have played only an collecting role in the conventional ECG monitoring system. However, to provide a real-time classification, the need of ECG classification in the embedded system has been introduced. Therefore, this paper reviews the existing ECG monitoring systems and provides a candidate solution for ECG classification in the embedded systems.",
keywords = "ECG, Embedded System, Holter, TinyML",
author = "Jaehyuk Kim and Eunchan Kim and Yeunwoong Kyung and Haneul Ko",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 13th International Conference on Information and Communication Technology Convergence, ICTC 2022 ; Conference date: 19-10-2022 Through 21-10-2022",
year = "2022",
doi = "10.1109/ICTC55196.2022.9952978",
language = "English",
series = "International Conference on ICT Convergence",
publisher = "IEEE Computer Society",
pages = "1671--1673",
booktitle = "ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence",
}