TABLE OF CONTENTS The artificial neural networks (ANNs) are regularly employed in EEG signal processing because of their effectiveness as pattern classifiers. In this chapter, four specific applications will be studied: On a day to day basis, ANNs can assist in identifying abnormal EEG activity in patients with neurological diseases such as epilepsy, Huntington's disease, and Alzheimer's disease. The ANNs can reduce the time taken for interpretation of physiological signals such as EEG, respiration, and ECG recorded during sleep. During an invasive surgical procedure, the ANNs can provide objective parameters derived from the EEG to help determine the depth of anesthesia. The ANNs have made significant contributions toward extracting embedded signals within the EEG which can be used to control external devices. This rapidly developing field, which is called braincomputer interface, has a large number of applications in empowering handicapped individuals to independently operate appliances, neuroprosthesis, or orthosis.
The electroencephalogram (EEG), generally recorded on the scalp from a number of electrodes, is the result of asynchronous firing of billions of neurons within the nervous system. Digital signal processing of the EEG has been...
