Detection and multichannel SVD-based filtering of trigeminal somatosensoryevoked potentials

Very weak and noisy trigeminal somatosensory evoked potentials (TSEPs) are considered, which are successfully evoked by electrical stimulation of the trigeminal nerve of 15 patients with endosseous oral implants. As TSEP anal ysis provides an objective means of assessing neuronal function, it is cons idered to be a promising tool for investigating tactile sensation through a nchoring implants in bone. For this purpose, a study of TSEP signals acquir ed from patients with endosseous oral implants has been carried out. Since TSEPs are severely contaminated by background ongoing electrical activities of the brain, a methodology is developed for statistically detecting the t ransient signal (TSEP) in the biological noise (EEG). For nine out of 15 pa tients, transient signals are defected in the background EEG activity. The TSEPs of these nine patients are subjected to further analysis. A multichan nel singular value decomposition (SVD)-based filtering method is applied wh ich successfully separates out the most energetic TSEPs from the background EEG, thereby increasing significantly the SNR of the recorded signals and improving extraction of the characteristic components of the TSEPs. It is s hown that the most prominent feature of the TSEP signals for patients with endosseous oral implants is a wave with peak latency between 9 and 15 ms, g enerally followed by a wave between 25 and 28 ms or 34 and 38 ms for the sp ecific cortical response areas.