Abstract:
This paper presents a hands-free head-movement
gesture classification system using a Neural Network employing
the Magnified Gradient Function (MGF) algorithm. The MGF
increases the rate of convergence by magnifying the first order
derivative of the activation function, whilst guaranteeing
convergence. The MGF is tested on able-bodied and disabled
users to measure its accuracy and performance. It is shown that
for able-bodied users, a classification improvement from
98.25% to 99.85% is made, and 92.08% to 97.50% for disabled
users.