Real time signal processing in the clinical setting.

Abstract

We routinely use a variety of real time signal acquisition, enhancement, and display techniques in the operating room to provide the surgeon with functional information. This enables reduction of surgical morbidity in cases which present a significant risk to the nervous system. Here we present regression based signal processing algorithms which produce considerable signal-to-noise-ratio enhancement with corresponding reduction in the time required to obtain an interpretable neurophysiological signal. We also present the approach we have applied to fault tolerance and distributed data display for our workstation cluster environment.