Real-Time Cardiac Abnormality Monitoring and Nursing for Patient Using Electrocardiographic Signals

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Ao, Huamin;Zhai, Enjian;Jiang, Le;Yang, Kailin;Deng, Yuxuan;...

通讯作者：

Ao, HM;Hao, Moujia;Chen, JP;Song, T;Ge, JW

作者机构：

[Ao, HM; Ao, Huamin] Fifth Hosp Daqing City, Daqing, Peoples R China.

[Zeng, Liuting; Zhai, Enjian; Yan, Yexing; Hao, Moujia; Deng, Yuxuan; Chen, Junpeng; Chen, JP; Yang, Kailin] Daqing Hosp Tradit Chinese Med, Dept Psychiat, Psychosomat Lab, Daqing, Peoples R China.

[Zhai, Enjian] Qingdao Univ Technol, Qingdao, Peoples R China.

[Jiang, Le] United World Coll East Africa Moshi Campus, Moshi, Tanzania.

[Yang, Kailin] Capital Med Univ, Beijing Anzhen Hosp, Beijing, Peoples R China.

通讯机构：

[Hao, MJ; Chen, JP ] D

[Ao, HM ] F

[Ge, JW ] H

[Song, T ] C

Fifth Hosp Daqing City, Daqing, Peoples R China.

语种：

英文

关键词：

Nursing;Electrocardiogram signals;Anomalous electrocardiogram monitoring;Machine learning;Neural networks

期刊：

CARDIOLOGY

ISSN：

0008-6312

年：

2024

DOI：

10.1159/000539767

基金类别：

Science and Technology Innovation Plan; Chinese Academy of Sciences [20194001882]

机构署名：

本校为其他机构

摘要：

Introduction Cardiovascular disease care is a critical clinical application that necessitates real-time monitoring models. Previous models required the use of multi-lead signals and could not be customized as needed. Traditional methods relied on manually designed supervised algorithms, based on empirical experience, to identify waveform abnormalities and classify diseases, and were incapable of monitoring and alerting abnormalities in individual waveforms. Methods This research reconstructed the vector model for arbitrary leads using the phase space time delay method, enabling the model to ar...

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Real-Time Cardiac Abnormality Monitoring and Nursing for Patient Using Electrocardiographic Signals

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