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Classification of motor commands using a modified self-organising feature map.

Sebelius, Fredrik LU ; Eriksson, L; Holmberg, Hans LU ; Levinsson, Anders LU ; Lundborg, Göran LU ; Danielsen, Nils LU ; Schouenborg, Jens LU ; Balkenius, Christian LU ; Laurell, Thomas LU and Montelius, Lars LU (2005) In Medical Engineering & Physics 27(5). p.403-413
Abstract
In this paper, a control system for an advanced prosthesis is proposed and has been investigated in two different biological systems: (1) the spinal withdrawal reflex system of a rat and (2) voluntary movements in two human males: one normal subject and one subject with a traumatic hand amputation. The small-animal system was used as a model system to test different processing methods for the prosthetic control system. The best methods were then validated in the human set-up. The recorded EMGs were classified using different ANN algorithms, and it was found that a modified self-organising feature map (SOFM) composed of a combination of a Kohonen network and the conscience mechanism algorithm (KNC) was superior in performance to the... (More)
In this paper, a control system for an advanced prosthesis is proposed and has been investigated in two different biological systems: (1) the spinal withdrawal reflex system of a rat and (2) voluntary movements in two human males: one normal subject and one subject with a traumatic hand amputation. The small-animal system was used as a model system to test different processing methods for the prosthetic control system. The best methods were then validated in the human set-up. The recorded EMGs were classified using different ANN algorithms, and it was found that a modified self-organising feature map (SOFM) composed of a combination of a Kohonen network and the conscience mechanism algorithm (KNC) was superior in performance to the reference networks (e.g. multi-layer perceptrons) as regards training time, low memory consumption, and simplicity in finding optimal training parameters and architecture. The KNC network classified both experimental set-ups with high accuracy, including five movements for the animal set-up and seven for the human set-up. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Medical Engineering & Physics
volume
27
issue
5
pages
403 - 413
publisher
Elsevier
external identifiers
  • PMID:15863349
  • WOS:000229899300006
  • Scopus:20944442083
ISSN
1873-4030
DOI
10.1016/j.medengphy.2004.09.008
language
English
LU publication?
yes
id
4a4ed4db-03c3-482a-9af1-82ed261cb0e2 (old id 138238)
alternative location
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=15863349&dopt=Abstract
date added to LUP
2007-07-03 16:07:21
date last changed
2016-10-13 04:30:38
@misc{4a4ed4db-03c3-482a-9af1-82ed261cb0e2,
  abstract     = {In this paper, a control system for an advanced prosthesis is proposed and has been investigated in two different biological systems: (1) the spinal withdrawal reflex system of a rat and (2) voluntary movements in two human males: one normal subject and one subject with a traumatic hand amputation. The small-animal system was used as a model system to test different processing methods for the prosthetic control system. The best methods were then validated in the human set-up. The recorded EMGs were classified using different ANN algorithms, and it was found that a modified self-organising feature map (SOFM) composed of a combination of a Kohonen network and the conscience mechanism algorithm (KNC) was superior in performance to the reference networks (e.g. multi-layer perceptrons) as regards training time, low memory consumption, and simplicity in finding optimal training parameters and architecture. The KNC network classified both experimental set-ups with high accuracy, including five movements for the animal set-up and seven for the human set-up.},
  author       = {Sebelius, Fredrik and Eriksson, L and Holmberg, Hans and Levinsson, Anders and Lundborg, Göran and Danielsen, Nils and Schouenborg, Jens and Balkenius, Christian and Laurell, Thomas and Montelius, Lars},
  issn         = {1873-4030},
  language     = {eng},
  number       = {5},
  pages        = {403--413},
  publisher    = {ARRAY(0x7d1f2f0)},
  series       = {Medical Engineering & Physics},
  title        = {Classification of motor commands using a modified self-organising feature map.},
  url          = {http://dx.doi.org/10.1016/j.medengphy.2004.09.008},
  volume       = {27},
  year         = {2005},
}