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The Application of Neural Networks to Interpret Evoked Potential Waveforms

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Artificial Neural Networks in Biomedicine

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

Abstract

The electrical activity of the neurones of the brain produce a continuous random time-varying electrical potential at the scalp known as the electroencephalogram (EEG). External stimuli or preparation for a task cause additional electrical scalp potentials known as evoked potentials (EPs). These typically last for hundreds of milliseconds and are an order of magnitude smaller in voltage compared with the EEG. It has been customary to enhance the EP (signal)-to-EEG (noise) ratio by averaging many individual trial recordings, and then to characterise the averaged EP in terms of its maximum and minimum (peak) values (amplitudes) and the times at which they occur (their latencies). These amplitudes and latencies are frequently modified in the case of abnormal brain conditions or by different psychiatric states, and they have therefore been used to study such conditions and states.

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Author information

Authors and Affiliations

  1. Sheffield-Hallam University, Sheffield, UK

    Barrie W. Jervis

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  1. Barrie W. Jervis
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Editor information

Editors and Affiliations

  1. School of Computing and Mathematical Sciences, Liverpool John Moore’s University, Liverpool, L3 3AF, UK

    Paulo J. G. Lisboa BSc, PhD

  2. School of Electronic, Communication and Electrical Engineering, University of Plymouth, Plymouth, UK

    Emmanuel C. Ifeachor BSc, MSc, PhD

  3. Institute of Computer Science, Technical University of Lodz, Lodz, Poland

    Piotr S. Szczepaniak MSc, PhD, DSc

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© 2000 Springer-Verlag London

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Jervis, B.W. (2000). The Application of Neural Networks to Interpret Evoked Potential Waveforms. In: Lisboa, P.J.G., Ifeachor, E.C., Szczepaniak, P.S. (eds) Artificial Neural Networks in Biomedicine. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0487-2_16

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  • DOI: https://doi.org/10.1007/978-1-4471-0487-2_16

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-005-7

  • Online ISBN: 978-1-4471-0487-2

  • eBook Packages: Springer Book Archive

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