A Neural Network for Recognizing Movement Patterns During Repetitive Self-Paced Movements of the Fingers in Opposition to the Thumb

Abstract

A data glove is a typical input device to control a virtual environment. At the same time it measures movements of wrist and fingers. The purposes of this investigation were to assess the ability of BrainMaker, a neural network, to recognize movement patterns during an opposition task that consisted of repetitive self-paced movements of the fingers in opposition to the thumb. The neural network contained 56 inputs, 3 hidden layers of 20 neurons, and one output. The 5th glove '95 (5DT), a commercial glove especially designed for virtual reality games, was used for finger motion capture. The training of the neural network was successful for recognizing the thumb, the index finger and the ring finger movements during the repetitive self-paced movements and neural network performed well during testing.