相关实验视频

Updated: Jun 14, 2025

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

3.6K

开发和验证一种实时服务模型,用于消除噪音和使用心电图信号对心律失常进行分类

Yeonjae Park1, You Hyun Park1,2, Hoyeon Jeong1

  • 1Department of Medical Informatics and Biostatistics, Graduate School, Yonsei University, Seoul 03722, Republic of Korea.

Sensors (Basel, Switzerland)
|August 29, 2024
PubMed
概括

这项研究引入了一个深度学习模型,用于从可穿戴式心电图 (ECG) 数据中准确检测心律失常. 该模型有效地消除噪音并对心律失常进行分类,改善了随时的心脏监测.

关键词:
心律失常的分类是心律失常的分类.电心电图可以消除噪音.生成性的对抗性网络.穿戴式设备是一种可穿戴的设备.

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