Recently, the micro-nano intelligent sports team from NEU Physical Education Department has made advancements in the field of intelligent sports equipment. Their research achievements were published in the Chemical Engineering Journal under the title of “A multi-sensor coupled supramolecular elastomer empowers intelligent monitoring of human gait and arch health”. Cheng Zihang, a 2023 master degree candidate in the field of sports science, is the first author, and Mao Yupeng, a specially-appointed researcher, is the corresponding author. NEU is listed as both the first and corresponding institution.
The micro-nano intelligent sports team is dedicated to in-depth research in the field of sports equipment engineering. By utilizing TENG sensing technology, the team efficiently captures the mechanical energy generated during human motion, enabling precise monitoring of human health and athletic training states. The innovative research of the team not only provides a new path of interdisciplinary integration for the development of wearable devices, but also strives to promote continuous progress in the field of sports technology. This research developed a motion monitoring system that combines supramolecular materials with Triboelectric Nanogenerator (TENG), demonstrating excellent performance in monitoring human gait and arch health.
Characteristics and applications of PGE elastomers
It is reported that the team has successfully prepared a supramolecular elastomer (PGE), which itself can act as a strain sensor to realize the precise monitoring of angular changes in multiple joints of the human body (including fingers, elbows, knees, ankles, etc.), with a response time of 75 milliseconds, which improves the real-time and accuracy of motion monitoring. Meanwhile, the PGE-TENG, constructed with PGE as the friction layer, is able to capture different motion behaviors and six basic gaits in real time, providing brand new data support for motion analysis.
Intelligent motion monitoring system based on machine learning
The team has developed an intelligent motion monitoring system based on machine learning algorithms. The system is able to accurately recognize the health status of human arch and the walking status of visually impaired people with accuracy rates of 97.5% and 99.6%, respectively, providing strong technical support for sports rehabilitation and assisted walking. This multi-sensor coupling research based on PGE elastomer and TENG realizes high-precision real-time monitoring of human motion, and also opens up a new way in the field of medical and health monitoring, and provides a new method to promote the integration of wearable devices and IoT technology.
