Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.
Identifieur interne : 002073 ( Ncbi/Checkpoint ); précédent : 002072; suivant : 002074Human-arm-and-hand-dynamic model with variability analyses for a stylus-based haptic interface.
Auteurs : Michael J. Fu [États-Unis] ; M Cenk Cavu O LuSource :
- IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society [ 1941-0492 ] ; 2012.
English descriptors
- KwdEn :
- MESH :
- instrumentation : Cybernetics.
- methods : Cybernetics.
- physiology : Arm, Hand, Hand Strength, Touch.
- Adult, Biomechanical Phenomena, Feedback, Female, Humans, Male, Man-Machine Systems, Models, Biological, Phantoms, Imaging.
Abstract
Haptic interface research benefits from accurate human arm models for control and system design. The literature contains many human arm dynamic models but lacks detailed variability analyses. Without accurate measurements, variability is modeled in a very conservative manner, leading to less than optimal controller and system designs. This paper not only presents models for human arm dynamics but also develops inter- and intrasubject variability models for a stylus-based haptic device. Data from 15 human subjects (nine male, six female, ages 20-32) were collected using a Phantom Premium 1.5a haptic device for system identification. In this paper, grip-force-dependent models were identified for 1-3-N grip forces in the three spatial axes. Also, variability due to human subjects and grip-force variation were modeled as both structured and unstructured uncertainties. For both forms of variability, the maximum variation, 95 %, and 67 % confidence interval limits were examined. All models were in the frequency domain with force as input and position as output. The identified models enable precise controllers targeted to a subset of possible human operator dynamics.
DOI: 10.1109/TSMCB.2012.2197387
PubMed: 22692923
Affiliations:
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pubmed:22692923Le document en format XML
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<author><name sortKey="Fu, Michael J" sort="Fu, Michael J" uniqKey="Fu M" first="Michael J" last="Fu">Michael J. Fu</name>
<affiliation wicri:level="2"><nlm:affiliation>Cleveland Functional Electrical Stimulation Center of Excellence, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH 44106, USA. mfu@fes.org</nlm:affiliation>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Cleveland Functional Electrical Stimulation Center of Excellence, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH 44106</wicri:regionArea>
<placeName><region type="state">Ohio</region>
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<author><name sortKey="Cavu O Lu, M Cenk" sort="Cavu O Lu, M Cenk" uniqKey="Cavu O Lu M" first="M Cenk" last="Cavu O Lu">M Cenk Cavu O Lu</name>
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<term>Cybernetics (methods)</term>
<term>Feedback</term>
<term>Female</term>
<term>Hand (physiology)</term>
<term>Hand Strength (physiology)</term>
<term>Humans</term>
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<term>Man-Machine Systems</term>
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<term>Biomechanical Phenomena</term>
<term>Feedback</term>
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<front><div type="abstract" xml:lang="en">Haptic interface research benefits from accurate human arm models for control and system design. The literature contains many human arm dynamic models but lacks detailed variability analyses. Without accurate measurements, variability is modeled in a very conservative manner, leading to less than optimal controller and system designs. This paper not only presents models for human arm dynamics but also develops inter- and intrasubject variability models for a stylus-based haptic device. Data from 15 human subjects (nine male, six female, ages 20-32) were collected using a Phantom Premium 1.5a haptic device for system identification. In this paper, grip-force-dependent models were identified for 1-3-N grip forces in the three spatial axes. Also, variability due to human subjects and grip-force variation were modeled as both structured and unstructured uncertainties. For both forms of variability, the maximum variation, 95 %, and 67 % confidence interval limits were examined. All models were in the frequency domain with force as input and position as output. The identified models enable precise controllers targeted to a subset of possible human operator dynamics.</div>
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<country name="États-Unis"><region name="Ohio"><name sortKey="Fu, Michael J" sort="Fu, Michael J" uniqKey="Fu M" first="Michael J" last="Fu">Michael J. Fu</name>
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