Rational design of self-powered sensors with polymer nanocomposites for human–machine interaction

Smart sensors are becoming one of the necessities for connecting and detecting surrounding stimuli with tremendous convenience, especially when exploiting a single powerful sensor with multifunctionality. To successfully accomplish the design of a self-powered sensor, serving power is becoming a critical issue because of its continuously consumed energy required by electronics. A variety of nanogenerators aiming for the rational design of self-powered system are reviewed and compared, followed by their recent advances with polymer nanocomposites for self-powered sensors. More importantly, the proposed conceptual design of a self-powered unit/device with triboelectric nanogenerator has been emphasized to eventually realize the practical activities towards multiple detections and human–machine interaction. Finally, challenges and new prospects of rational design of self-powered polymer composite sensors in achieving human–machine interaction/interface are discussed.     

基于可穿戴惯性测量的滑雪运动员姿态测量与水平评估方法

运动量化分析是科学化滑雪训练的重要发展方向,而滑雪过程中人体运动模式的数字化表达是科学量化分析的基础和依据.设计并搭建了基于可穿戴MEMS惯性测量单元的人体运动捕捉与姿态重构系统,结合人体多刚体运动模型实现了滑雪过程的人体重构,并应用于高山滑雪运动中回转动作的辅助训练.同时,针对基于多自由度模拟滑雪训练平台的室内训练场景,提出了一种适用于滑雪回转运动的数字化评估方法.该方法利用动作捕捉系统和姿态重构系统提取滑行者五种滑行特征数据,并通过与高水平运动员运动参数的相似性度量和线性拟合实现对滑雪运动员技术参数的评估,以辅助科学训练.最后在室内Olymp模拟滑雪训练台上进行实验,验证了该方法的有效性.