Independent mobility is an important element for children's development and beneficial in helping them acquire physical and intellectual activities. Unfortunately, existing interface devices for powered wheelchairs are inaccessible to individuals with muscular impairment of their upper/lower limbs or who have involuntary movements of their extremities. This research aims to develop an autonomous mobility device, which adapts the self-learning system to personal characteristic movements. This device incorporates a light sensor to reduce the physical burden and uses a learning algorithm, such as a neural network system. In this paper, we describe the measurement of the user's movement, the establishment of a neural network system, which discriminates the target movement, and the overall system evaluation.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com