Artificial Intelligence of Things Wearable System for Cardiac Disease Detection

Yu Jin Lin, Chen Wei Chuang, Chun Yueh Yen, Sheng Hsin Huang, Peng Wei Huang, Ju Yi Chen, Shuenn Yuh Lee

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

This study proposes an artificial intelligence of things (AIoT) system for electrocardiogram (ECG) analysis and cardiac disease detection. The system includes a front-end IoT-based hardware, a user interface on smart device's application (APP), a cloud database, and an AI platform for cardiac disease detection. The front-end IoT-based hardware, a wearable ECG patch that includes an analog front-end circuit and a Bluetooth module, can detect ECG signals. The APP on smart devices can not only display users' real-time ECG signals but also label unusual signals instantly and reach real-time disease detection. These ECG signals will be uploaded to the cloud database. The cloud database is used to store each user's ECG signals, which forms a big-data database for AI algorithm to detect cardiac disease. The algorithm proposed by this study is based on convolutional neural network and the average accuracy is 94.96%. The ECG dataset applied in this study is collected from patients in Tainan Hospital, Ministry of Health and Welfare. Moreover, signal verification was also performed by a cardiologist.

原文English
主出版物標題Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
發行者Institute of Electrical and Electronics Engineers Inc.
頁面67-70
頁數4
ISBN(電子)9781538678848
DOIs
出版狀態Published - 2019 三月
事件1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 - Hsinchu, Taiwan
持續時間: 2019 三月 182019 三月 20

出版系列

名字Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

Conference

Conference1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
國家Taiwan
城市Hsinchu
期間19-03-1819-03-20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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