A Sensor-Based Hand Gesture Recognition System for Japanese Sign Language

Xianzhi Chu, Jiang Liu, Shigeru Shimamoto

20212021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)43 citationsDOI

Abstract

In this paper, we propose a sensor-based data acquisition glove for Japanese Sign Language (JSL) hand gesture recognition. Five flex sensors, an Inertial Measurement Unit (IMU), and three Force Sensing Resistors (FSRs) are used to detect the bending degree of fingers and hand movement information. The detected data are transmitted to the computer by an Arduino Micro. The average accuracy of the hand gesture recognition for a single subject, using the Support Vector Machine (SVM) based and the Dynamic Time Wrapping (DTW) based algorithm are 96.9% and 94.5%, respectively. Our proposed system also achieves an average recognition accuracy of about 82.5% for the cross-recognition among three subjects. The experimental results indicate that our proposed system has great potential for JSL hand gesture recognition.

Topics & Concepts

Gesture recognitionGestureComputer scienceSign languageSupport vector machineInertial measurement unitSpeech recognitionArtificial intelligenceArduinoWired gloveComputer visionPattern recognition (psychology)Embedded systemLinguisticsPhilosophyHand Gesture Recognition SystemsGaze Tracking and Assistive TechnologyRobotics and Automated Systems