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Pattern recognition of nerve signals using an artificial neural network

Montelius, L. (author)
Lund University,Lunds universitet,Fasta tillståndets fysik,Fysiska institutionen,Institutioner vid LTH,Lunds Tekniska Högskola,Solid State Physics,Department of Physics,Departments at LTH,Faculty of Engineering, LTH
Sebelius, F. (author)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH
Eriksson, L. (author)
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Holmberg, H. (author)
Schouenborg, J. (author)
Lund University,Lunds universitet,Neurofysiologi,Forskargrupper vid Lunds universitet,Neurophysiology,Lund University Research Groups
Danielsen, N. (author)
Lund University,Lunds universitet,Neurala gränsytor,Forskargrupper vid Lunds universitet,Neuronano Research Center (NRC),Neural Interfaces,Lund University Research Groups
Wallman, L. (author)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Neuronano Research Center (NRC),Forskargrupper vid Lunds universitet,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH,Lund University Research Groups
Laurell, T. (author)
Lund University,Lunds universitet,Avdelningen för Biomedicinsk teknik,Institutionen för biomedicinsk teknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Biomedical Engineering,Departments at LTH,Faculty of Engineering, LTH
Balkenius, C. (author)
Lund University,Lunds universitet,Kognitiv modellering,Forskargrupper vid Lunds universitet,Kognitionsvetenskap,Filosofiska institutionen,Institutioner,Humanistiska och teologiska fakulteterna,Cognitive modeling,Lund University Research Groups,Cognitive Science,Department of Philosophy,Departments,Joint Faculties of Humanities and Theology
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 (creator_code:org_t)
1996
1996
English.
In: ; , s. 1502-1503
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • By using a microfabricated nerve chip with integrated electrodes through which peripheral nerves can generate and make electrical connects, it should be possible to control a remote prosthesis by processing the detected nerve signals. In this study different artificial neural networks have been employed for classification of such complex patterns of signals. The signals were obtained from four electrodes detecting muscle activity in a rat hindlimb as a consequence of applied stimulus to the rat right hindpaw. These signals recorded at four different sites resembles a situation of a nerve chip with four electrodes, which implies that we might be able to use the same strategy when analyzing data from a four-electrode chip to obtain information from the nervous system. In this paper we will address the usefulness of different network topologies for analyzing measured in-vivo data from an implanted perforated nerve chip.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinsk bioteknologi -- Medicinsk bioteknologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Medical Biotechnology -- Medical Biotechnology (hsv//eng)

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