Human movement monitoring and behavior recognition for intelligent sports using customizable and flexible triboelectric nanogenerator

Effective collection,recognition,and analysis of sports information is the key to intelligent sports,which can help athletes to improve their skills and formulate scientific training plans and competition strategies.At present,wearable electronic devices used for movement monitoring still have some limitations,such as high cost and energy consumption,incompatibility of suitable flexibility and personalized spatial structure,dissatisfactory data analysis methods,etc.In this work,a novel three-dimensionalprinted thermoplastic polyurethane is introduced as the elastic shell and friction layer,and it endows the proposed customizable and flexible triboelectric nanogenerator(CF-TENG)with personalized spatial structure and robust correlation to external pressure.In practical application,it exhibits highly sensitive responses to the joint-bending motion of the finger,wrist,or elbow.Furthermore,a pressure-sensing insole and smart ski pole based on CF-TENG are manufactured to build a comprehensive sports monitoring system to transmit the athletes’motion information from feet and hands through the plantar pressure distribution and ski pole action.To recognize the movement status,the self-developed automatic peak recognition algorithm(P-Find)and machine learning algorithm(subspace K-Nearest Neighbors)were introduced to accurately distinguish the four typical motion behaviors and three primary sub-techniques of cross-country skiing,with accuracy rates of 98.2%and 100%.This work provides a novel strategy to promote the personalized applications of TENGs in intelligent sports.

Arrayed piezoresistive and inertial measurement unit sensor-integrated assistant training tennis racket for multipoint hand pressure monitoring and representative action recognition

Technology-assisted ball training systems have become a research hotspot due to their ability to provide quantitative data for guiding athletes to address their areas of improvement.However,traditional tennis training systems still have some limitations;for instance,they are subjective,expensive,heavy,and time-consuming.In this research,an assistant training tennis racket,which consists of arrayed flexible sensors and an inertial measurement unit,has been proposed to comprehensively analyze the representative actions’force and acceleration.Consisting of MXene as the sensitive material and melamine sponge as the substrate(named MMSS),the flexible sensor exhibited an excellent sensitivity of 5.35 kPa^(-1)(1.1-22.2 kPa)due to the formation of a 3D conductive network.Moreover,the sensor retained a high sensitivity of 0.6 k Pa-1in an ultrawide measurement range(22.2-266 kPa).In addition to recognizing the type of hitting action,an artificial intelligence algorithm was introduced to accurately differentiate the five typical motion behaviors with an accuracy rate of 98.2%.This study not only proposes a comprehensive assistant training tennis racket for improving the techniques of tennis enthusiasts but also a new information processing scheme for intelligent sensing and distinction of different movements,which can offer significant application potential in sports big data collection and the Internet of things.

Intelligent self-powered sensor based on triboelectric nanogenerator for take-off status monitoring in the sport of triplejumping

In the era of big data and the Internet of Things,the digital information of athletes is particularly significant in sports competitions.Here,an intelligent self-powered take-off board sensor(TBS)based on triboelectric nanogenerator(TENG)with a solid-wooden substrate is provided for precise detection of athletes’take-off status in the sport of triple-jumping,which is sufficient for triplejumping training judgment with a high accuracy of 1 mm.Meanwhile,a foul alarm system and a distance between the athlete’s foot and take-off line(GAP)measurement system are further developed to provide take-off data for athletes and referees.The induced charges are formed by the TBS during taking-off,and then the real-time exercise data is acquired and processed via the test program.This work presents a self-powered sports sensor for intelligent sports monitoring and promotes the application of TENG-based sensors in intelligent sports.