Literature DB >> 7275404

Experience with Swedish multifunctional prosthetic hands controlled by pattern recognition of multiple myoelectric signals.

C Almström, P Herberts, L Körner.   

Abstract

Clinical experience with two types of multifunctional prosthetic hand, controlled by pattern recognition of multiple myoelectric signals is reported. The prostheses have been used for between one and five years by five patients. The pattern recognition control system enabled the patients to control six separate movements accurately after a short period of training. One of the tested prostheses, the SVEN-hand, was not reliable enough to allow clinical use outside the laboratory. The ES-hand, a second generation multifunctional prosthesis, has promising features, being self-contained and fast moving. It is concluded that multi-functional prosthetic hands help amputees to avoid tiresome and awkward compensatory movements. Their scope, however, does not extend beyond that of conventional myoelectric prostheses. Their combined movements are cosmetically more appealing than a single three-point grip. In order to gain wider acceptance, multifunctional prosthetic hands must reach a state of development comparable to conventional myoelectric devices particularly with regard to weight and compactness. A pattern recognition control system is essential to the design.

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Year:  1981        PMID: 7275404     DOI: 10.1007/BF00286094

Source DB:  PubMed          Journal:  Int Orthop        ISSN: 0341-2695            Impact factor:   3.075


  6 in total

1.  Hand prosthesis control via myoelectric patterns.

Authors:  P Herberts; C Almström; R Kadefors; P D Lawrence
Journal:  Acta Orthop Scand       Date:  1973

2.  Ideas on sensory feedback in hand prostheses.

Authors:  P Herberts; L Körner
Journal:  Prosthet Orthot Int       Date:  1979-12       Impact factor: 1.895

3.  Clinical application study of multifunctional prosthetic hands.

Authors:  P Herberts; C Almström; K Caine
Journal:  J Bone Joint Surg Br       Date:  1978-11

4.  [Functional myoelectric prostheses. Acceptance among unilateral below-elbow amputees].

Authors:  K Caine; P Herberts; L Wensby; L Körner
Journal:  Lakartidningen       Date:  1980-02-27

5.  Myocoder-computer study of electromyographic patterns.

Authors:  F R Finley; R W Wirta
Journal:  Arch Phys Med Rehabil       Date:  1967-01       Impact factor: 3.966

6.  Clinical application study of externally powered upper-limb prosthetics systems: the VA elbow, the VA hand, and the VA/NU myoelectric hand systems.

Authors:  E A Lewis; C R Sheredos; T T Sowell; V L Houston
Journal:  Bull Prosthet Res       Date:  1975
  6 in total
  6 in total

1.  Improving myoelectric pattern recognition robustness to electrode shift by changing interelectrode distance and electrode configuration.

Authors:  Aaron J Young; Levi J Hargrove; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2011-11-29       Impact factor: 4.538

2.  Cognitive vision system for control of dexterous prosthetic hands: experimental evaluation.

Authors:  Strahinja Dosen; Christian Cipriani; Milos Kostić; Marco Controzzi; Maria C Carrozza; Dejan B Popović
Journal:  J Neuroeng Rehabil       Date:  2010-08-23       Impact factor: 4.262

3.  Implantable myoelectric sensors (IMESs) for intramuscular electromyogram recording.

Authors:  Richard F ff Weir; Phil R Troyk; Glen A DeMichele; Douglas A Kerns; Jack F Schorsch; Huub Maas
Journal:  IEEE Trans Biomed Eng       Date:  2009-01       Impact factor: 4.538

4.  A comparison of the effects of electrode implantation and targeting on pattern classification accuracy for prosthesis control.

Authors:  Todd R Farrell; Richard F Ff Weir
Journal:  IEEE Trans Biomed Eng       Date:  2008-09       Impact factor: 4.538

Review 5.  On the viability of implantable electrodes for the natural control of artificial limbs: review and discussion.

Authors:  Max Ortiz-Catalan; Rickard Brånemark; Bo Håkansson; Jean Delbeke
Journal:  Biomed Eng Online       Date:  2012-06-20       Impact factor: 2.819

6.  User adaptation in Myoelectric Man-Machine Interfaces.

Authors:  Janne M Hahne; Marko Markovic; Dario Farina
Journal:  Sci Rep       Date:  2017-06-30       Impact factor: 4.379

  6 in total

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