生物识别
可穿戴计算机
材料科学
认证(法律)
可穿戴技术
脉搏(音乐)
生物医学工程
人工智能
计算机科学
医学
嵌入式系统
计算机安全
电信
探测器
作者
Keyu Meng,Zixiao Liu,Xiao Xiao,Farid Manshaii,Pei Li,Junyi Yin,Haiyan Wang,Haixia Mei,Yubo Sun,Ximin He,Jun Yang,Jun Chen
标识
DOI:10.1002/adfm.202403163
摘要
Abstract The measurement accuracy of current wearable pulse sensors is grandly challenged by motion artifacts caused by body biomechanical activities. In this study, a honeycomb‐structure‐inspired wearable pulse sensor is reported which not only performs ambulant cardiovascular monitoring but also realizes biometric authentication utilizing the acquired individual pulse wave profiles. The sensor showcases an impressive sensitivity of 46.2 mV Pa −1 , a swift response time of 21 ms, and exceptional durability (minimal degradation after 6000 cycles). For practical application in clinical settings, the sensor is able to record pulse signals continuously and accurately from individuals aged between 27 and 57 years, especially including a 29‐year‐old pregnant woman. Leveraging deep learning algorithms, the sensor further utilizes individual pulse wave profiles for biometric authentication, reaching a classification accuracy of up to 99.4%. The honeycomb‐structure‐inspired wearable pulse sensor marks a significant advancement in the field of practical cardiovascular monitoring and biometric authentication.
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