Research On EEG Analysis In Biofeedback And Its Application On Epilepsy

Epilepsy is a common serious neurological disorder. Approximately 1% of the world population suffers from this chronic disease, among them about 25% are intractable to current medical and/or surgical therapies. For these patients, EEG biofeedback (also called neurofeedback) is an effective therapy that can help in seizure control. To assess the effects of EEG biofeedback on brain electrophysiology and to determine how biofeedback works, different EEG measurements are applied to explore the variations in EEG signals recorded from epileptic patients taking biofeedback training.21 patients with intractable epilepsy were trained to increase production of sensorimotor rhythm (SMR, 12–15 Hz) activity and decrease production of theta (4–8 Hz) wave activity with one scalp electrode placed on the position C4. The treatment effective rate was 76.2%. To evaluate the effects of the treatment using EEG analysis, 16-channel EEG recordings of six patients were acquired before a patient received biofeedback training and after about 10 training sessions, others were acquired at different times over the treatment duration.In this dissertation, the EEG power spectral density (PSD) was used to evaluate the differences in EEG signals before and after biofeedback. After sessions of treatment, the EEG SMR to theta PSD ratio calculated from the C4 electrode site became larger than that before treatment, which agrees well with the biofeedback protocol. This result verified the self-regulatory mechanism of neurofeedback, so that we could evaluate the efficacy of neurofeedback from a new perspective other than the reduction of seizure frequency.Since nolinear EEG measurements can reflect more information in changes of brain function state than linear measurements, the variations of approximate entropy (ApEn) and correlation dimension (D2) were also explored. The results demonstrated that the ApEn and D2 over the 16-channel EEG recordings all increased about one month later compared with those of the EEG recordings before training. This reveals that biofeedback training can increase the degree of random electrical activity of the cortical neuron population, so that the symptoms of epilepsy are improved and seizures alleviated. Thus the ApEn and D2 criterions can be used to evaluate the effect of EEG biofeedback. It may give an indication of the electrophysiologic basis of EEG biofeedback.A set of EEG biofeedback system was developed, which has functions of EEG signal acquisition, threshold setting, feature extraction, animation and mp3 playing, system and patient database management and so on. Nonlinear EEG measurements were incorporated into this biofeedback system, which mainly consists of linear frequency parameters at present. The result of system testing proves that the system could satisfy the requirements of biofeedback training.