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Journal article

穿戴式心电监测中的 AI 计算

Alternative title:
Artificial intelligence in wearable electrocardiogram monitoring
Abstract:
心电监测在心血管疾病诊断、预防、康复中具有重要的临床价值。随着物联网、大数据、云计算、 人工智能(AI)等科技的快速发展,穿戴式心电正扮演着越来越重要的角色。伴随人口老龄化进程加剧,心血管 病防治模式升级愈发紧迫,利用 AI 技术辅助临床解析长程心电进而提高心血管病早期检测和风险预警能力,成 为智慧医疗领域的一个重要方向。穿戴式心电智能监测需要监测终端和云端的协同智能,同时医疗应用场景的 明确有助于穿戴式心电监测的精准实施。本文首先总结了心电领域相关的 AI 技术研究和应用进展,然后通过三 个案例阐述了穿戴式心电监测中 AI 计算如何与临床进行协同,最后探讨了心电 AI 研究的两个核心问题—— AI 技术的可靠性和价值,并展望了心电 AI 发展的机遇和未来挑战。

[Electrocardiogram (ECG) monitoring owns important clinical value in diagnosis, prevention and rehabilitation of cardiovascular disease (CVD). With the rapid development of Internet of Things (IoT), big data, cloud computing, artificial intelligence (AI) and other advanced technologies, wearable ECG is playing an increasingly important role. With the aging process of the population, it is more and more urgent to upgrade the diagnostic mode of CVD. Using AI technology to assist the clinical analysis of long-term ECGs, and thus to improve the ability of early detection and prediction of CVD has become an important direction. Intelligent wearable ECG monitoring needs the collaboration between edge and cloud computing. Meanwhile, the clarity of medical scene is conducive for the precise implementation of wearable ECG monitoring. This paper first summarized the progress of AI-related ECG studies and the current technical orientation. Then three cases were depicted to illustrate how the AI in wearable ECG cooperate with the clinic. Finally, we demonstrated the two core issues-the reliability and worth of AI-related ECG technology and prospected the future opportunities and challenges.]
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.7507/1001-5515.202301032

Authors

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Role:
Author
ORCID:
0000-0002-9502-4472
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-1572-6192


Publisher:
West China Medical Publishers
Journal:
Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering More from this journal
Volume:
40
Issue:
6
Pages:
1084-1092
Publication date:
2023-12-13
DOI:
ISSN:
1001-5515
Pmid:
38151930


Language:
Chinese
Keywords:
Pubs id:
2129053
Local pid:
pubs:2129053
Deposit date:
2026-02-03
ARK identifier:

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