Classification of brain-stem trigeminal evoked potentials in multiple sclerosis, minor head injuries and post-concussion syndrome pathologies by similarity measurements

In this study measurements obtained from brain-stem trigeminal evoked poten tials (BTEP) are applied to the problem of diagnosing Multiple Sclerosis (M S) and Post-concussion syndrome (PCS), We present a simplistic model that d epicts the BTEP waveform as the linear combination of a set of filters exci ted by a short stimulus. The relation between the BTEP latencies and the Is t to 4th harmonic components is shown. The performance of a fuzzy similarit y measure based classifier is compared with that of human experts. The effi ciency of the proposed classifier in conjunction with delay time and amplit ude features is examined, Using this novel approach, a classification rate of 93.55% and 84.1% for MS and PCS pathologies, respectively, was achieved, This performance compares favorably to the classification rates of 84.28% for MS and 70.47% for PCS pathologies achieved by human experts. (C) 2000 E lsevier Science Ireland Ltd. All rights reserved.