Recognising Irish Sign Language Using Electromyography

Abstract

Sign language is the non-verbal communication used by people with hearing and speaking impairments. The automatic recognition of sign languages is usually based on video analysis of the signer though this is difficult when considering different light levels or the surrounding environment. The work in this paper uses electromyography (EMG) and focuses on letters of the Irish Sign Language (ISL) alphabet. EMG is the recording of the electrical activity produced to stimulate movement in the skeletal muscles. We capture muscle signals and inertial movement data using the Thalmic MYO armband and, in real time, recognise the ISL alphabet. Our implementation is based on signal processing, feature extraction and machine learning. The only input required to translate the ISL gestures are EMG and movement data, thus our approach is usable in scenarios where using video for automatic recognition video is not possible.

Artificial Intelligence Technologies for Sign Language

“…On the other hand, wearable sensors have been adopted for capturing sign language gestures. Galea et al in [ 20 ], used electromyography (EMG) to capture electrical activity that was produced during arm movement. The Thalmic MYO armband device was used for the recording of Irish sign language alphabet.…”

Development of Sign Language Motion Recognition System for Hearing-Impaired People Using Electromyography Signal

“…As a meaning to construct individual communication, sign languages do not share the same standard worldwide. Instead, cultural difference along with other factors create a huge difference among the sign languages [ 3 , 4 , 5 , 6 ]. The physical component of sign languages usually consists of movement of forearm and hand motion.…”