Classification of Auditory Evoked Potentials based on the wavelet decomposition and SVM network

Abstract

For electrophysiological hearing assessment and diagnosis of brain stem lesions, the most often used are auditory brainstem evoked potentials of short latency. They are characterized by successively arranged maxima as a function of time, called waves. Morphology of the course, in particular, the timing and amplitude of each wave, allow a neurologist to make diagnose, what is not an easy task. A neurologist should be experienced, concentrated, and should have very good perception. In order to support his diagnostic process, the authors have developed an algorithm implementing the automated classification of auditory evoked potentials to the group of pathological and physiological cases, the sensitivity and specificity determined for an independent test group (of 50 cases) of respectively 84% and 88%.[b]Keywords[/b]: biomedical engineering, brainstem auditory evoked potentials, wavelet decomposition, support vector machine

Keywords

• biomedical engineering
• brainstem auditory evoked potentials
• Wavelet decomposition
• support vector machine