Neural network training of artificial humanoid hands for deaf-blind sign language

Peter Scarfe, Euan Lindsay

Research output: Book chapter/Published conference paper › Conference paper

Abstract

The paper presents a concept for the design of a humanoid hand to be trained in deaf-blind sign language. A brief history of humanoid hands is discussed, followed by an overview of the first Curtin humanoid hand. Extending on several key concepts of the first Curtin hand, a new design is put forward together with key design concepts that will be essential for training the new hand deaf-blind sign language. Such design concepts include the use of Artificial Neural Networks to provide natural control of a biomechanical system to reproduce human movement, together with the use of data gloves to train the neural networks deaf-blind sign language. Finally a brief look at the other deaf-blind signing hands is presented, together with the significance of the research.

Original languageEnglish
Title of host publication12th Annual Conference on Mechatronics and Machine Vision in Practice, M2VIP 2005
Pages112-119
Number of pages8
Publication statusPublished - 2005
Event12th Annual IEEE Conference Mechatronics and Machine Vision in Practice, M2VIP 2005 - Manila, Philippines
Duration: 29 Nov 2005 → 01 Dec 2005

Conference

Conference12th Annual IEEE Conference Mechatronics and Machine Vision in Practice, M2VIP 2005
CountryPhilippines
CityManila
Period29/11/05 → 01/12/05

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    • Cite this

    Scarfe, P., & Lindsay, E. (2005). Neural network training of artificial humanoid hands for deaf-blind sign language. In 12th Annual Conference on Mechatronics and Machine Vision in Practice, M2VIP 2005 (pp. 112-119)