State-of-the-Art in Data Gloves: A Review of Hardware, Algorithms, and Applications

Abstract

Data glove is one of the devices that can express human intention via detecting hand motion with high-precision. In recent years, flourished applications have been driven by data gloves from human-machine interaction (HMI) to biomedical sciences. To understand the latest research status and grasp the development direction, this study provides a systematic overview of the state-of-the-art for data gloves. Specifically, we take the research topics of hardware design, algorithms for gesture recognition, and the application areas as the entry point. Detailed elaboration of key algorithms techniques, from data processing to classification, for hand gesture recognition is made and quantitative analysis of the recent research achievements is summarized. We found that hand motion detection with data gloves is mostly employed for gesture recognition, and the majority of studies are focused on the performance validation of the gesture recognition, in particular for static gestures. A systematic illustration of the current research challenges as well as the future directions of related data gloves are finally discussed.