Hands-free control of power wheelchairs using Bayesian neural network classification

Publication Type:
Conference Proceeding
2004 IEEE Conference on Cybernetics and Intelligent Systems, 2004, pp. 745 - 749
Issue Date:
Filename Description Size
2004001203.pdf668.4 kB
Adobe PDF
Full metadata record
This paper describes the formulation and implementation of Bayesian neural networks for head-movement classification in a hands-free wheelchair navigation system. Bayesian neural network training adjusts the weight decay parameters automatically to their near-optimal values that give the best generalisation. Moreover, no separate validation set is used so all available data can be used for training. Experimental results are presented showing that Bayesian neural network can classify the head movement accurately.
Please use this identifier to cite or link to this item: