Using fractal analysis to improve switching rates in "hands free" environmental control technology for the severely disabled

A negative impact on the quality of life of the severely neurologically disordered such as spinal cord injured persons is the loss of the ability to control devices in their immediate environment. Consequently, we have conducted research on technology designed to restore some measure of independence by providing hands free control over these devices by using EEG signals associated with eye closure (EC) and eye opening (EO). In a previous study we demonstrated that the nonlinear technique fractal dimension analysis was a viable alternative to spectral analysis in detecting these signals in the EEG of able bodied persons. This paper explores the efficacy of using fractal dimension to detect EC/EO signals in a spinal cord injured population. The fractal dimension method was found to improve from the standard spectral analysis technique in that there was a significant reduction is the occurrence of false positive and false negative switching. This improved detection of EC/EO in the brain activity of severely disabled people will be utilised in our technology for remote switching of electrical devices