Human-Computer Interaction System with Artificial Neural Network Using Motion Tracker and Data Glove

Abstract

A Human-Computer Interaction (HCI) system has been developed with an Artificial Neural Network (ANN) using a motion tracker and a data glove. The HCI system is able to recognize American Sign Language letter and number gestures. The finger joint angle data obtained from the strain gauges in the sensory glove define the hand shape while the data from the motion tracker describe the hand position and orientation. The data flow from the sensory glove is controlled by a software trigger using the data from the motion tracker during signing. Then, the glove data is processed by a recognition neural network.

Department(s)

Mechanical and Aerospace Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2005 Springer Verlag, All rights reserved.

Publication Date

01 Jan 2005

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