Next Article in Journal
Assessment of Retrieved N2O, NO2, and HF Profiles from the Atmospheric Infrared Ultraspectral Sounder Based on Simulated Spectra
Previous Article in Journal
A Survey on the Roadmap to Mandate on Board Connectivity and Enable V2V-Based Vehicular Sensor Networks
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessReview
Sensors 2018, 18(7), 2208; https://doi.org/10.3390/s18072208

A Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art between 2007 and 2017

1
Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak 35900, Malaysia
2
Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit 34001, Iraq
*
Author to whom correspondence should be addressed.
Received: 15 April 2018 / Revised: 5 June 2018 / Accepted: 9 June 2018 / Published: 9 July 2018
(This article belongs to the Section Physical Sensors)

Abstract

Loss of the ability to speak or hear exerts psychological and social impacts on the affected persons due to the lack of proper communication. Multiple and systematic scholarly interventions that vary according to context have been implemented to overcome disability-related difficulties. Sign language recognition (SLR) systems based on sensory gloves are significant innovations that aim to procure data on the shape or movement of the human hand. Innovative technology for this matter is mainly restricted and dispersed. The available trends and gaps should be explored in this research approach to provide valuable insights into technological environments. Thus, a review is conducted to create a coherent taxonomy to describe the latest research divided into four main categories: development, framework, other hand gesture recognition, and reviews and surveys. Then, we conduct analyses of the glove systems for SLR device characteristics, develop a roadmap for technology evolution, discuss its limitations, and provide valuable insights into technological environments. This will help researchers to understand the current options and gaps in this area, thus contributing to this line of research. View Full-Text
Keywords: sign language; glove; sensor; gesture recognition; pattern recognition; man-machine interface (MMI); classification sign language; glove; sensor; gesture recognition; pattern recognition; man-machine interface (MMI); classification
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Ahmed, M.A.; Zaidan, B.B.; Zaidan, A.A.; Salih, M.M.; Lakulu, M.M. A Review on Systems-Based Sensory Gloves for Sign Language Recognition State of the Art between 2007 and 2017. Sensors 2018, 18, 2208.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top