A Self‐Powered Dual Ratchet Angle Sensing System for Digital Twins and Smart Healthcare
Chao Liu, Rui Gu, Jiahong Yang, Lin Luo, Mingxia Chen, Yao Xiong, Ziwei Huo, Yang Liu, Keteng Zhang, Jie Gong, Wei Liang, Yanqiang Lei, Zhong Lin Wang, Qijun Sun
Abstract
Abstract In the swiftly progressing landscape of wearable electronics and the Internet of Things (IoTs), there is a burgeoning demand for devices that are lightweight, cost‐effective, and self‐powered. In this study, a self‐powered bidirectional knee joint motion monitoring system is introduced, leveraging a dual ratchet sensing (DRS) system fabricated using 3D printing technology. This approach offers substantial economic and portability benefits. The DRS system is engineered to harness the negative work generated from knee joint movements to power commercial electronic devices, obviating the need for additional metabolic energy from the human body. By synergizing the DRS with virtual reality technology, it becomes feasible to monitor knee joint movements in real‐time with remarkable accuracy, presenting a novel avenue for the integration of digital twin technology. Through the amalgamation of convolutional neural network machine learning algorithms with Bayesian optimization techniques, the DRS system can discern up to 97% of knee joint movements, paving the way for innovative applications in smart rehabilitation and healthcare.