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http://dx.doi.org/10.7472/jksii.2019.20.6.137

A Comparative Study on the Optimal Model for abnormal Detection event of Heart Rate Time Series Data Based on the Correlation between PPG and ECG  

Kim, Jin-soo (Dept. of Computer Engineering, Gachon University)
Lee, Kang-yoon (Dept. of Computer Engineering, Gachon University)
Publication Information
Journal of Internet Computing and Services / v.20, no.6, 2019 , pp. 137-142 More about this Journal
Abstract
This paper Various services exist to detect and monitor abnormal event. However, most services focus on fires and gas leaks. so It is impossible to prevent and respond to emergency situations for the elderly and severely disabled people living alone. In this study, AI model is designed and compared to detect abnormal event of heart rate signal which is considered to be the most important among various bio signals. Specifically, electrocardiogram (ECG) data is collected using Physionet's MIT-BIH Arrhythmia Database, an open medical data. The collected data is transformed in different ways. We then compare the trained AI model with the modified and ECG data.
Keywords
Photoplethysmography(PPG); Electrocardiogram(ECG); Abnormal event detection; SVM; LSTM;
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