Title :
Automatic peak identification in auditory evoked potentials with the use of artificial neural networks
Author :
van Gils, M.J. ; Cluitmans, P.J.M.
Author_Institution :
Div. of Med. Electr. Eng., Eindhoven Univ. of Technol., Netherlands
Abstract :
In this research artificial neural network (ANN) based feature extractors were investigated on their suitability to automate the assessment of the location of characteristic peaks in auditory evoked potentials (AEPs). Five types of feature extractors were tested on their ability to determine the latency of peak V and peak Pa in AEPs. The performance on peak V proved to be satisfactory, for the identification of peak Pa improvement is still desired
Keywords :
auditory evoked potentials; AEP; ANN based feature extractors; Kohonen self-organizing map; artificial neural networks; auditory evoked potentials; automatic peak identification; characteristic peaks; latency; peak Pa; peak V; Artificial neural networks; Delay; Feature extraction; Gas insulated transmission lines; Humans; Intelligent networks; Medical diagnostic imaging; Monitoring; Multilayer perceptrons; Prototypes;
Conference_Titel :
Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-2050-6
DOI :
10.1109/IEMBS.1994.415341
