Ambulatory Cardiovascular Monitoring Via a Machine-Learning-Assisted Textile Triboelectric Sensor.
Ambulatory Cardiovascular Monitoring Via a Machine-Learning-Assisted Textile Triboelectric Sensor.
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DOI：
10.1002/adma.202104178
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发表时间：
2021-10
影响因子：
29.4
通讯作者：
Chen, Jun
中科院分区：
文献类型：
--
作者：
Fang, Yunsheng;Zou, Yongjiu;Xu, Jing;Chen, Guorui;Zhou, Yihao;Deng, Weili;Zhao, Xun;Roustaei, Mehrdad;Hsiai, Tzung K.;Chen, Jun
关键词：
可穿戴生物电子学用于连续和可靠地监测人体运动和汗液的脉搏波仍然是一个巨大的挑战和高度期望。在这里，开发了一种低成本、轻质、机械耐用的纺织品摩擦电传感器，可以将动脉搏动引起的微小皮肤变形转换为电能，用于在流动和出汗的环境中进行高保真和连续的脉搏波形监测。该传感器的信噪比为23.3dB，响应时间为40ms，灵敏度为0.21μA kpa−1。在机器学习算法的辅助下，纺织摩擦电传感器可以连续、精确地测量收缩压和舒张压，并通过医院的商业血压袖带验证了其准确性。此外，还开发了基于内置算法的定制手机应用程序(APP)，用于一键健康数据共享和数据驱动的心血管诊断。纺织摩擦电传感器无线生物监测系统有望为物联网时代心血管系统的连续和个性化表征提供一种实用的范例。
Wearable bioelectronics for continuous and reliable pulse wave monitoring against body motion and perspiration remains a great challenge and highly desired. Here, a low-cost, lightweight, and mechanically durable textile triboelectric sensor that can convert subtle skin deformation caused by arterial pulsatility into electricity for high-fidelity and continuous pulse waveform monitoring in an ambulatory and sweaty setting is developed. The sensor holds a signal-to-noise ratio of 23.3 dB, a response time of 40 ms, and a sensitivity of 0.21 μA kPa−1. With the assistance of machine learning algorithms, the textile triboelectric sensor can continuously and precisely measure systolic and diastolic pressure, and the accuracy is validated via a commercial blood pressure cuff at the hospital. Additionally, a customized cellphone application (APP) based on built-in algorithm is developed for one-click health data sharing and data-driven cardiovascular diagnosis. The textile triboelectric sensor enabled wireless biomonitoring system is expected to offer a practical paradigm for continuous and personalized cardiovascular system characterization in the era of the Internet of Things.
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