Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
Adv Mater. 2021 Oct;33(41):e2104178. doi: 10.1002/adma.202104178. Epub 2021 Aug 31.
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 . 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.
可穿戴式生物电子设备可用于连续可靠地监测脉搏波，以抵抗身体运动和出汗，这仍然是一个巨大的挑战，也是人们非常渴望实现的目标。在这里，开发了一种低成本、轻量级、机械耐用的纺织摩擦电传感器，它可以将动脉搏动引起的皮肤细微变形转换为电能，以便在活动和出汗的环境中进行高保真和连续的脉搏波监测。该传感器的信噪比为 23.3dB，响应时间为 40ms，灵敏度为 0.21µA kPa。借助机器学习算法，纺织摩擦电传感器可以连续、精确地测量收缩压和舒张压，其准确性在医院通过商业血压袖带进行了验证。此外，还开发了一个基于内置算法的定制手机应用程序 (APP)，用于一键式健康数据共享和数据驱动的心血管诊断。基于纺织摩擦电传感器的无线生物监测系统有望为物联网时代的连续个性化心血管系统特征提供实用范例。
