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

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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. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Oz, C., & Leu, M. C. (2005). Human-computer interaction system with artificial neural network using motion tracker and data glove. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3776 LNCS, pp. 280–286). https://doi.org/10.1007/11590316_40

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