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受中医启发的全印刷软压力传感器阵列,具有自适应加压功能,用于高度可靠的个性化长期脉搏诊断。

Traditional Chinese Medicine (TCM)-Inspired Fully Printed Soft Pressure Sensor Array with Self-Adaptive Pressurization for Highly Reliable Individualized Long-Term Pulse Diagnostics.

作者信息

Wang Xin, Wu Guirong, Zhang Xikuan, Lv Fei, Yang Zekun, Nan Xueli, Zhang Zengxing, Xue Chenyang, Cheng Huanyu, Gao Libo

机构信息

Pen-Tung Sah Institute of Micro-Nano Science and Technology, Xiamen University, Xiamen, 361102, China.

Shenzhen Research Institute of Xiamen University, Xiamen University, Shenzhen, 518000, China.

出版信息

Adv Mater. 2025 Jan;37(1):e2410312. doi: 10.1002/adma.202410312. Epub 2024 Sep 30.

Abstract

Reliable, non-invasive, continuous monitoring of pulse and blood pressure is essential for the prevention and diagnosis of cardiovascular diseases. However, the pulse wave varies drastically among individuals or even over time in the same individual, presenting significant challenges for the existing pulse sensing systems. Inspired by pulse diagnosis methods in traditional Chinese medicine (TCM), this work reports a self-adaptive pressure sensing platform (PSP) that combines the fully printed flexible pressure sensor array with an adaptive wristband-style pressure system can identify the optimal pulse signal. Besides the detected pulse rate/width/length, "Cun, Guan, Chi" position, and "floating, moderate, sinking" pulse features, the PSP combined with a machine learning-based linear regression model can also accurately predict blood pressure such as systolic, diastolic, and mean arterial pressure values. The developed diagnostic platform is demonstrated for highly reliable long-term monitoring and analysis of pulse and blood pressure across multiple human subjects over time. The design concept and proof-of-the-concept demonstrations also pave the way for the future developments of flexible sensing devices/systems for adaptive individualized monitoring in the complex practical environments for personalized medicine, along with the support for the development of digital TCM.

摘要

可靠、无创、连续地监测脉搏和血压对于心血管疾病的预防和诊断至关重要。然而,脉搏波在个体之间甚至同一个体的不同时间内都有很大差异,这给现有的脉搏传感系统带来了重大挑战。受中医脉诊方法的启发,这项工作报告了一种自适应压力传感平台(PSP),该平台将全印刷柔性压力传感器阵列与自适应腕带式压力系统相结合,能够识别最佳脉搏信号。除了检测到的脉搏率/宽度/长度、“寸、关、尺”位置以及“浮、中、沉”脉象特征外,PSP与基于机器学习的线性回归模型相结合,还能够准确预测收缩压、舒张压和平均动脉压等血压值。所开发的诊断平台已被证明可对多个人类受试者的脉搏和血压进行长期高度可靠的监测和分析。该设计理念和概念验证演示也为未来在复杂实际环境中用于个性化医疗的自适应个性化监测的柔性传感设备/系统的发展铺平了道路,同时也为数字中医的发展提供了支持。

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