Human-Computer interaction system with artificial neural network using motion tracker and data glove

Authors:
Cemil Oz;Ming C. Leu
Affiliations:
Department of Mechanical and Aerospace Engineering, University of Missouri-Rolla, Rolla, Missouri;Department of Mechanical and Aerospace Engineering, University of Missouri-Rolla, Rolla, Missouri
Venue:
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
Year:
2005

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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.