Suppr超能文献

受折纸启发的可拉伸驻极体传感器用于帕金森震颤的分析与评估

Kirigami-Inspired Stretchable Piezoelectret Sensor for Analysis and Assessment of Parkinson's Tremor.

作者信息

Xie Qisen, Han Liuyang, Liu Jie, Zhang Wenjie, Zhao Liuyan, Liu Yuhan, Chen Yanru, Li Yuzhen, Zhou Qian, Dong Ying, Wang Xiaohao

机构信息

Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.

出版信息

Adv Healthc Mater. 2025 Jan;14(1):e2402010. doi: 10.1002/adhm.202402010. Epub 2024 Nov 22.

Abstract

Human muscle activity contains rich information that can reflect human movement patterns and conditions of diseases or physical abnormalities. Flexible pressure sensors enable the assessment of muscle tremors in Parkinson's disease (PD) through Force Myography (FMG). Here, an easily fabricated, ultra-sensitive, and stretchable piezoelectret pressure sensor is presented. Utilizing an effective integration of Kirigami structure and piezoelectret air gap, the sensor achieved a dynamic sensitivity of ≈725 pC/N (@5 Hz), measurement repeatability of <2.5%, measurement hysteresis of <1%, a pressure detection limit of <15 Pa, a response time of ≈2.5 ms, stable output within ±3% over 40 000 cycles, and output decay of <2.5% after 1000 cycles of complex deformation, meeting non-distorted measurement conditions up to 20 Hz. Successful monitoring and assessment of hand muscle tremors are demonstrated. Furthermore, using a 1×3 sensor array enabled tremor localization, achieving a high accuracy rate of 99.5% with machine learning algorithms. Additionally, the sensor facilitated the experimental quantification and assisted scoring of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), with an accuracy of ≈85%. The sensor demonstrates potential for assisting in the diagnosis and rehabilitation monitoring of Parkinson's disease.

摘要

人体肌肉活动包含丰富信息,可反映人体运动模式以及疾病状况或身体异常情况。柔性压力传感器能够通过测力肌电图(FMG)评估帕金森病(PD)中的肌肉震颤。在此,我们展示了一种易于制造、超灵敏且可拉伸的驻极体压力传感器。通过将剪纸结构与驻极体气隙有效集成,该传感器实现了约725皮库仑/牛顿(@5赫兹)的动态灵敏度、小于2.5%的测量重复性、小于1%的测量滞后、小于15帕斯卡的压力检测极限、约2.5毫秒的响应时间、在40000次循环内±3%的稳定输出以及在1000次复杂变形循环后小于2.5%的输出衰减,满足高达20赫兹的无失真测量条件。成功展示了对手部肌肉震颤的监测与评估。此外,使用1×3传感器阵列实现了震颤定位,借助机器学习算法准确率高达99.5%。此外,该传感器有助于对运动障碍协会统一帕金森病评定量表(MDS - UPDRS)进行实验量化和辅助评分,准确率约为85%。该传感器展示了在帕金森病诊断和康复监测方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/706d/11694081/07ac62e81b6b/ADHM-14-0-g005.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验