A Multi-functional Electronic Glove for Multidimensional Environmental Perception and Gesture Recognition

Abstract

In recent years, wearable electronic gloves with rich sensing functions have garnered widespread attention. Researchers are exploring various aspects of wearable devices including structural design, material innovation, and algorithm optimization. An analysis of demand suggests that wearable electronic gloves should possess sensory functions like hand, which includes roughness of contacted objects, assessing temperature of touched objects, determining grasp force, and interpreting gesture language. This paper presents a multi-sensing wearable flexible electronic glove equipped with graphene foam material sensors that can perceive external pressure, roughness, temperature, and express gesture language. The experimental results show that this glove exhibits excellent approximately linear-range sensing characteristics for force perception (1.475 kPa-1 at 0-0.4 kPa), outstanding temperature sensing capability (temperature sensitivity is -1.22% within the range of 30-80℃), and recognition judgment of 12 different gestures. Additionally, an optimized KNN (K-nearest neighbor) algorithm based on time-domain window is proposed. Compared with traditional KNN algorithm, KNN based on time-domain window improves the accuracy of gesture intent recognition from 86.15% to 91.93%. Wearable electronic gloves represent promising developments for fields such as hand rehabilitation training for patients, intention expression for individuals suffering from language barriers, and wearable multifunctional sensing applications.