The Amazing Digital Gloves That Give Voice to the Voiceless

Glove-based systems represent one of the most important efforts aimed at acquiring hand movement data. Generally dumb people use sign language for communication but they find difficulty in communicating with others who do not understand sign language. It is based on the need of developing an electronic device that can translate sign language into speech in order to make the communication take place between the mute communities with the general public possible, a Wireless data gloves is used which is normal cloth driving gloves fitted with flex sensors along the length of each finger and the thumb. Mute people can use the gloves to perform hand gesture and it will be converted into speech so that normal people can understand their expression. This paper provides the map for developing such a digital glove. It also analyzes the characteristics of the device and discusses future wok. A foremost goal of this paper is to provide readers with a basis for understanding glove system technology used in biomedical science.

[1]  Kosuke Sato,et al.  Real-time gesture recognition by learning and selective control of visual interest points , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Seong-Whan Lee Automatic gesture recognition for intelligent human-robot interaction , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[3]  Masumi Ishikawa,et al.  Recognition of a hand-gesture based on self-organization using a DataGlove , 1999, ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on Neural Information Processing. Proceedings (Cat. No.99EX378).

[4]  Yael Edan,et al.  Cluster labeling and parameter estimation for the automated setup of a hand-gesture recognition system , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[5]  Mohammad Al-Amin Bhuiyan,et al.  On Gesture Recognition for Human-Robot Symbiosis , 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.

[6]  Ho-Sub Yoon,et al.  Hand gesture recognition using hidden Markov models , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[7]  Aaron F. Bobick,et al.  Parametric Hidden Markov Models for Gesture Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Mohammed Yeasin,et al.  Improving continuous gesture recognition with spoken prosody , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[9]  Hong Li,et al.  Multi-scale gesture recognition from time-varying contours , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.