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Artificial neural networks in EEG analysis
Chapter

Artificial neural networks in EEG analysis

Abstract

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 brain-computer interface, has a large number of applications in empowering handicapped individuals to independently operate appliances, neuroprosthesis, or orthosis. © 2006, Idea Group Inc.

Authors

Kamath MV; Upton AR; Wu J; Bajaj HS; Poehlman S; Spaziani R

Book title

Neural Networks in Healthcare Potential and Challenges

Pagination

pp. 177-194

Publication Date

December 1, 2006

DOI

10.4018/978-1-59140-848-2.ch008
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