[Artificial intelligence in wearable electrocardiogram monitoring]

Abstract

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.

Keywords: Artificial intelligence; Electrocardiogram monitoring; Smart medical; Wearable electrocardiogram.

图 1

Development diagram for the technology and product of AI and ECG monitoring AI与心电监测技术和产品发展脉络图

图 2

Two main technical routes of AI research for ECG analysis at present 目前心电AI研究的两条主要技术路线

图 3

AF burden assessment using AF localization in long-term single-lead ECGs of a patient with paroxysmal AF 阵发性房颤患者长程单导心电数据中基于房颤定位的房颤负荷评估

图 4

Prediction of the results of 6-minute walk test by wearable ECGs combined with activity and physiological data 通过穿戴式心电数据、活动数据和个人生理数据预测6分钟步行测试结果

图 5

Multi-modal sensing in sleep monitoring 睡眠监测中的多模数据传感

图 6

Collaborative framework for the edge and cloud intelligence in wearable ECG monitoring 穿戴式心电终端侧智能与云端侧智能协同框架