MobiGesture: Mobility-aware hand gesture recognition for healthcare

Abstract

Abstract Accurate recognition of hand gestures while moving is still a significant challenge, which prevents the wide use of existing gesture recognition technology. In this paper, we propose a novel mobility-aware hand gesture segmentation algorithm to detect and segment hand gestures. We also propose a Convolutional Neural Network (CNN) to classify hand gestures with mobility noises. Based on the segmentation and classification algorithms, we develop MobiGesture, a mobility-aware hand gesture recognition system for healthcare. For the leave-one-subject-out cross-validation test, experiments with human subjects show that the proposed segmentation algorithm achieves 94.0% precision, and 91.2% recall when the user is moving. The proposed hand gesture classification algorithm is 16.1%, 15.3%, and 14.4% more accurate than state-of-the-art work when the user is standing, walking and jogging, respectively.