Multifunctional Textile Electronics Based on Triboelectric Nanogenerator with Electrochemical Synergy for Parkinson’s Disease Management

纳米发生器 可穿戴技术 可穿戴计算机 桥(图论) 计算机科学 持续监测 摩擦电效应 数码产品 纳米传感器 智能传感器 稳健性(进化) 疾病 嵌入式系统 鉴定(生物学) 接口(物质) 桥接(联网) 临床诊断 航空航天 人工智能 人机交互 柔性电子器件 医学
作者
Hongwei Chu,Qiuqian Ou,Liangling Cai,Zhenhe Huang,H Wang,Yue Hu,Y L Liu,Jiyu Li,Yuyu Gao,Linhui Shen,J S Liu,Y Y Li,Xinge Yu
出处
期刊:Advanced Fiber Materials [Springer Science+Business Media]
卷期号:8 (5): 2062-2078
标识
DOI:10.1007/s42765-026-00727-w
摘要

Parkinson’s disease (PD) affects tens of millions of people globally, yet current clinical management remains fragmented, relying on subjective assessments and episodic laboratory measurements that fail to capture disease dynamics in real-world settings. Here, we present a smart textile-integrated multimodal interface (STMI) that seamlessly combines tremor quantification with real-time therapeutic drug monitoring through a wearable wristband platform. The system integrates an array of enhanced triboelectric nanogenerators with optimized bead-on-string nanofiber architecture for sensitive tremor detection, coupled with fiber-based electrochemical sensors for simultaneous monitoring of levodopa (LD), pH, and sodium levels in sweat. By leveraging deep learning algorithms (bidirectional LSTM), the STMI achieves accurate discrimination between healthy controls, prodromal Parkinson’s patients, and PD patients—including early detection of prodromal stages currently undetectable by standard imaging. Longitudinal tracking in PD patients demonstrates real-time correlation between tremor suppression and LD pharmacokinetics, enabling quantitative assessment of medication efficacy and identification of wearing-off phenomena. The textile-based form factor ensures ergonomic wearability and mechanical robustness for continuous monitoring, while the integrated multimodal sensing paradigm establishes a new standard for personalized PD management. This work demonstrates how intelligent wearable systems can bridge the gap between motor symptom assessment and pharmacological profiling, transforming PD care from episodic clinical visits to continuous, data-driven therapeutic optimization.
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