Abstract:

BACKGROUND: The cortical slow potential and its shift changes are present in all individuals. Based on slow cortical potentials and variation detection of neural cortex (motor area) brain mapping method can avoid the missed detection. Detailed studies on this aspect have been rarely reported.
OBJECTIVE: To investigate the characteristics of principle and feasibility of cortical electroencephalogram (EEG) slow cortical potentials for the intraoperative neural cortex (motor area) function.
METHODS: Brain cortex in the (motor) functional area of finger cortical areas of the cortex EEG data from 3 patients of Harbour Hospital was collected, and the corresponding finger bending motion data were collected as self-control. Wavelet decomposition and reconstruction of signals, extraction of sports event-related slow cortical potentials before and after the incident in the movement of energy (ERP indicators) as the characteristic parameter were performed, followed by construction of a particular threshold to classify. The outcome data were compared with the corresponding movement in bending finger, and the rate of correct detection was determined. The pilot data collected were divided into training and test groups, respectively for feature selection algorithms based classifier design and performance analysis.
RESULTS AND CONCLUSION: With a slow cortical potential target as the characteristic ERP signal volume and 1.6 as the threshold for classification, the correct detection rate of classification and positioning was 84%. Cortex (motor area) slow potential feature extraction and classification can be more effective for motor cortex localization with detection of high resolution, to avoid missed benefits.