Abstract
Visual evoked potentials (VEPs) are a useful tool in the diagnosis of multiple sclerosis. To improve their diagnostic power in the early stages of the disease, the VEP shape, as well as its latency, were considered. The Karhunen-Loeve expansion (KLE) was used because it affords an unique advantage in classifying the VEPs by their shape, and gives a well-defined criterion based on similarity to the normative prototype. Using this criterion, it was possible to quantitatively define normative limits of waveform. We were also able to detect early changes in VEPs recorded from suspected multiple sclerosis patients. KLE promises to enable classification of waveforms in early stages of the pathology, when peak-latency comparisons are the least effective.