Research of Virtual Nerve Induce Electrical Signal Auto-check Technology

AIM: Epilepsy neurons in the brain caused by abnormal discharge or part of the overall dysfunction of the brain characterized by chronic diseases, simulated biological visual perception system, according to the sparse neuronal response characteristics of the high-risk population for epilepsy nervous system electrophysiological screening, early detection and intervention of the relevant population, reduce the extent of involvement of epilepsy and maiming, death rate. Methods: Selecting the suitable decomposition of matching pursuit algorithm, with new atomic less to rebuild normal EEG and specific types of diseases EEG, the convenience of the various diseases of the nervous system - the characteristics of EEG identification and extraction. Results: Treatment 16-Standard EEG, isolated from epilepsy wave characteristics, and to identify characteristics of wave to be in the diagnosis of epilepsy, epilepsy basis of this characteristic wave reflected strikes into the 16-standard electrode, the relevant sources of electricity bit software localization of epileptic foci preliminary. Conclusion: Sparse representation model can obtain EEG signals that an effective method of EEG signals through the effective component machine identification, summed up the series features wave patterns for clinical diagnostic information, which reduces the workload of epilepsy signal recognition, enhanced the efficiency and accuracy of identifying and realizing the scale of epilepsy screening.