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User training for pattern-recognition based myoelectric prostheses using a serious game

Kristoffersen, Morten Bak; Franzke, Andreas; Murgia, Alessio; van der Sluis, Corry; Bongers, Raoul M.


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  <identifier identifierType="DOI">10.5281/zenodo.1209334</identifier>
  <creators>
    <creator>
      <creatorName>Kristoffersen, Morten Bak</creatorName>
      <givenName>Morten Bak</givenName>
      <familyName>Kristoffersen</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-3901-2856</nameIdentifier>
      <affiliation>University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, the Netherlands</affiliation>
    </creator>
    <creator>
      <creatorName>Franzke, Andreas</creatorName>
      <givenName>Andreas</givenName>
      <familyName>Franzke</familyName>
      <affiliation>University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, the Netherlands</affiliation>
    </creator>
    <creator>
      <creatorName>Murgia, Alessio</creatorName>
      <givenName>Alessio</givenName>
      <familyName>Murgia</familyName>
      <affiliation>University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, the Netherlands</affiliation>
    </creator>
    <creator>
      <creatorName>van der Sluis, Corry</creatorName>
      <givenName>Corry</givenName>
      <familyName>van der Sluis</familyName>
      <affiliation>University of Groningen, University Medical Center Groningen, Department of Rehabilitation Medicine, Groningen, the Netherlands</affiliation>
    </creator>
    <creator>
      <creatorName>Bongers, Raoul M.</creatorName>
      <givenName>Raoul M.</givenName>
      <familyName>Bongers</familyName>
      <affiliation>University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, the Netherlands</affiliation>
    </creator>
  </creators>
  <titles>
    <title>User training for pattern-recognition based myoelectric prostheses using a serious game</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2017</publicationYear>
  <subjects>
    <subject>Serious games</subject>
    <subject>User training</subject>
    <subject>Motor learning</subject>
    <subject>Prosthesis</subject>
    <subject>Myocontrol</subject>
    <subject>Pattern-recognition</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2017-05-08</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Presentation</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1209334</alternateIdentifier>
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    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/ecfunded</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="info:eu-repo/semantics/closedAccess">Closed Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;BACKGROUND&lt;br&gt;
Individuals with upper-limb deficiency who are fitted&lt;br&gt;
with a prosthesis are normally trained in the use of&lt;br&gt;
such device. During training pattern-recognition based&lt;br&gt;
control, the way training improves control skills and&lt;br&gt;
what kind of feedback facilitates skill acquisition is&lt;br&gt;
still poorly understood. Moreover no training protocols&lt;br&gt;
for pattern-recognition control have been described in&lt;br&gt;
the literature that do not require an expert trainer which&lt;br&gt;
limits the clinical applicability of pattern-recognition&lt;br&gt;
controlled prosthetics.&lt;br&gt;
AIM&lt;br&gt;
The aim of this study is to investigate how different&lt;br&gt;
kinds of feedback improve the control skills of patternrecognition&lt;br&gt;
control.&lt;br&gt;
METHOD&lt;br&gt;
Nine able-bodied volunteers participated in an&lt;br&gt;
initial experiment in which they either performed&lt;br&gt;
conventional system training or gamified system&lt;br&gt;
training with no prior user training. Based on the results&lt;br&gt;
of the initial experiment, a follow-up experiment will&lt;br&gt;
be conducted where four different kinds of training&lt;br&gt;
regimes are investigated namely; conventional training&lt;br&gt;
with knowledge of results but without coaching,&lt;br&gt;
conventional training with knowledge of results and&lt;br&gt;
knowledge of performance, serious game training or&lt;br&gt;
training with no feedback (control). Each group will&lt;br&gt;
include 15 participants, who train one hour per day for&lt;br&gt;
five consecutive days. Offline and online accuracy as&lt;br&gt;
well as the repeatability index, separability index and&lt;br&gt;
mean semi-principal axis [1] will be reported for each&lt;br&gt;
group.&lt;br&gt;
RESULTS&lt;br&gt;
In the initial experiment control performance was&lt;br&gt;
measured using the motion test [2] and a questionnaire&lt;br&gt;
was used to measure the participants experience of&lt;br&gt;
the system training and evaluation. No significant&lt;br&gt;
differences were found between the groups.&lt;br&gt;
Preliminary results of the follow-up experiment will&lt;br&gt;
also be reported.&lt;br&gt;
DISCUSSION &amp;amp; CONCLUSION&lt;br&gt;
The finding that no differences were found between&lt;br&gt;
the groups in the initial experiment could be ascribed&lt;br&gt;
to the way the game targets were set in the gamified&lt;br&gt;
system training and to an unintuitive mapping&lt;br&gt;
between movement and game control. In the followup&lt;br&gt;
experiment that will be performed a fixed mapping&lt;br&gt;
inspired by Radhakrishnan et. al [3] is used where the&lt;br&gt;
electromyogram measured at each electrode located on&lt;br&gt;
the forearm is mapped to a direction.&lt;br&gt;
REFERENCES&lt;br&gt;
1. Bunderson NE et. al, IEEE T Neur Sys Reh. 2012&lt;br&gt;
2. Kuiken TA et. al, J Am Med Assoc. 2009&lt;br&gt;
3. Radhakrisnan S. et. al, J Neurophysiol. 2008&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/687795/">687795</awardNumber>
      <awardTitle>Intuitive Natural Prosthesis UTilization</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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