Bio-Inspired Techniques in Human-Computer Interface for Control of Assistive Devices-Reference-Cited by-同舟云学术

Bio-Inspired Techniques in Human-Computer Interface for Control of Assistive Devices

Published:2018 Issue: Volume: Page:23-46
ISSN:2328-1316
Container-title:Advances in Human and Social Aspects of Technology
language:
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Author:

Geethanjali P.¹

Affiliation:

1. VIT University, India

Abstract

Most of the assistive devices are of user contact based control like body-powered prosthetic hand, joystick control of wheelchair, sip-and-puff, etc. and have a limited number of control movements. The performance of these assistive devices improves using bio-signals/gesture based control embedded in the processor. Gesture based control is widely used in wheelchair navigation control, communication with external world for neuromuscular impaired subjects. On the other hand, bio-signals are used widely in prosthetic devices, wheelchair control, orthotic devices, etc. with pattern recognition based control strategy. The choice and number of features used in pattern recognition for accurate control of assistive device is crucial. Further, these features performance also varies with the classifier. The appropriate selection of combination of pattern recognition will enhance the accuracy. This chapter focuses on bio-inspired techniques in selection of features and classification for the pattern recognition based assistive device control.

Publisher

IGI Global

Reference39 articles.

1. Barrero, V., Grisales, E. V., Rosas, F., Sanchez, C., & Leon, J. (2001). Design and implementation of an intelligent interface for myoelectric controlled prosthesis. In Proceedings of the 23rd Annual International Conference of the IEEE. Istanbul, Turkey: IEEE.

2. A study of back-propagation and radial basis neural network on EMG signal classification. In Proceedings of the;Y. L.Chong;6th International Symposium,2009

3. Del, B. A., & Park, D. C. (1994). Myoelectric signal recognition using fuzzy clustering and artificial neural networks in real time. In Proceedings of the IEEE World Congress on Computational Intelligence and Neural Networks. IEEE.

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