AI-based detection for Remote Electrocardiogram Monitoring System

With the rapid advancement of artificial intelligence (AI) and remote patient monitoring technologies, there is a growing interest in developing robust and efficient AI-based detection systems for cardiac arrhythmias. This study presents the implementation of an AI-driven arrhythmia detection system...

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Bibliographic Details
Published in2024 IEEE World AI IoT Congress (AIIoT) pp. 336 - 341
Main Authors Garcia, Max, Kumar, Sanjeev
Format Conference Proceeding
LanguageEnglish
Published IEEE 29.05.2024
Subjects
AI-based detection
Analytical models
Arrhythmia
Artificial intelligence
Data models
ECG
Electrocardiography
Remote Patient Monitoring
Security attacks
Servers
Telehealth
Training
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DOI10.1109/AIIoT61789.2024.10578986

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Summary:With the rapid advancement of artificial intelligence (AI) and remote patient monitoring technologies, there is a growing interest in developing robust and efficient AI-based detection systems for cardiac arrhythmias. This study presents the implementation of an AI-driven arrhythmia detection system utilizing the MIT-BIH Arrhythmia Database which not only classifies normal and abnormal ECG segments but also detects bad-read segments caused by network data attacks.
DOI:10.1109/AIIoT61789.2024.10578986