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.
Recommended Citation
C. Oz and M. Leu, "Human-Computer Interaction System with Artificial Neural Network Using Motion Tracker and Data Glove," Proceedings of the 1st International Conference on Pattern Recognition and Machine Intelligence, Springer Verlag, Jan 2005.
The definitive version is available at https://doi.org/10.1007/11590316_40
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