A Wearable System for Recognizing American Sign Language in Real-Time Using IMU and Surface EMG Sensors.

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A Wearable System for Recognizing American Sign Language in Real-Time Using IMU and Surface EMG Sensors.

IEEE J Biomed Health Inform. 2016 Aug 25;

Authors: Wu J, Sun L, Jafari R

Abstract
A Sign Language Recognition (SLR) system translates signs performed by deaf individuals into text/speech in real time. Inertial measurement unit (IMU) and surface electromyography (sEMG) are both useful modalities to detect hand/arm gestures. They are able to capture signs and the fusion of these two complementary sensor modalities will enhance system performance. In this paper, a wearable system for recognizing American Sign Language (ASL) in real-time is proposed, fusing information from an inertial sensor and sEMG sensors. An information gain based feature selection scheme is used to select the best subset of features from a broad range of well-established features. Four popular classification algorithms are evaluated for 80 commonly used ASL signs on four subjects. The experimental results show 96.16% and 85.24% average accuracies for intra-subject and intra-subject cross session evaluation respectively, with the selected feature subset and a support vector machine classifier. The significance of adding sEMG for American Sign Language recognition is explored and the best channel of sEMG is highlighted.

PMID: 27576269 [PubMed - as supplied by publisher]

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