Study of Sign Language Recognition Using Wearable Sensors

Boon Giin Lee, Wan Young Chung

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


Sign language was designed to allow hearing-impaired person to interact with others. Nonetheless, sign language was not a common practice in the society which produce difficulty in communication with hearing-impaired community. The general existing studies of sign language recognition applied computer vision approach; but the approach was limited by the visual angle and greatly affected by the background lightning. In addition, computer vision involved machine learning (ML) that required collaboration work from team of expertise, along with utilization of high expense hardware. Thus, this study aimed to develop a smart wearable American Sign Language (ASL) interpretation model using deep learning method. The proposed model applied sensor fusion to integrate features from six inertial measurement units (IMUs). Five IMUs were attached on top of the each fingertip whereas an IMU was placed on the back of the hand’s palm. The study revealed that ASL gestures recognition with derived features including angular rate, acceleration and orientation achieved mean true sign recognition rate of 99.81%. Conclusively, the proposed smart wearable ASL interpretation model was targeted to assist hearing-impaired person to communicate with society in most convenient way possible.

Original languageEnglish
Title of host publicationIntelligent Human Computer Interaction - 12th International Conference, IHCI 2020, Proceedings
EditorsMadhusudan Singh, Dae-Ki Kang, Jong-Ha Lee, Uma Shanker Tiwary, Dhananjay Singh, Wan-Young Chung
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages9
ISBN (Print)9783030684488
Publication statusPublished - 2021
Event12th International Conference on Intelligent Human Computer Interaction, IHCI 2020 - Daegu, Korea, Republic of
Duration: 24 Nov 202026 Nov 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12615 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Conference on Intelligent Human Computer Interaction, IHCI 2020
Country/TerritoryKorea, Republic of


  • Deep learning
  • Human computer interaction
  • Sensor fusion
  • Sign language
  • Wearable

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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