可穿戴计算机
计算机科学
信号(编程语言)
忠诚
生物电子学
干扰(通信)
可穿戴技术
人工智能
纳米技术
频道(广播)
电信
材料科学
嵌入式系统
生物传感器
程序设计语言
作者
Sicheng Chen,Qunle Ouyang,Xianglin Meng,Yibo Yang,Can Li,Xuan-Bo Miao,Zehua Chen,Ganggang Zhao,Yaguo Lei,Bernard Ghanem,Sandeep Gautam,Jianlin Cheng,Zheng Yan
出处
期刊:Science Advances
[American Association for the Advancement of Science (AAAS)]
日期:2025-04-02
卷期号:11 (14): eadv2406-eadv2406
被引量:11
标识
DOI:10.1126/sciadv.adv2406
摘要
Soft bioelectronics enable noninvasive, continuous monitoring of physiological signals, essential for precision health care. However, capturing biosignals during physical activity, particularly biomechanical signals like cardiac mechanics, remains challenging due to motion-induced interference. Inspired by starfish’s pentaradial symmetry, we introduce a starfish-like wearable bioelectronic system designed for high-fidelity signal monitoring during movement. The device, featuring five flexible, free-standing sensing arms connected to a central electronic hub, substantially reduces mechanical interference and enables high-fidelity acquisition of cardiac electrical (electrocardiogram) and mechanical (seismocardiogram and gyrocardiogram) signals during motion when coupled with signal compensation and machine learning. Using these three cardiac signal types as inputs, machine learning models deployed on smart devices achieve real-time, high-accuracy (more than 91%) diagnoses of heart conditions such as atrial fibrillation, myocardial infarction, and heart failure. These findings open previously undiscovered avenues by leveraging bioinspired device concepts combined with cutting-edge data science to boost bioelectronic performance and diagnostic precision.
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