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dc.contributor.advisorNeville Hogan.en_US
dc.contributor.authorCharles, Steven Knighten_US
dc.contributor.otherHarvard University--MIT Division of Health Sciences and Technology.en_US
dc.date.accessioned2009-06-25T20:35:26Z
dc.date.available2009-06-25T20:35:26Z
dc.date.copyright2008en_US
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/45623
dc.descriptionThesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2008.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionIncludes bibliographical references (p. 173-178).en_US
dc.description.abstractOver the past three decades, much research in motor neuroscience has focused on understanding how humans make coordinated reaching movements, yielding valuable insight into the planning and control of reaching movements, and establishing a foundation for robot-assisted rehabilitation. The goal of this doctoral research was to provide a quantitative characterization of humans' wrist rotations, paving the way for intelligent robot-assisted wrist rehabilitation. More specifically, we have characterized the kinematics, dynamics, and adaptation of wrist rotations, and discussed implications for planning and control. Kinematics: It is well known that humans make relatively straight reaching movements, suggesting that reaching movements are primarily under kinematic control of hand position. We used a motion capture system to test if wrist rotations are also under kinematic control. We found that wrist rotations exhibit a pattern with significantly more path curvature and variability than reaching movements (p = 0.001). While the increased path curvature could indicate that wrist rotations are not under kinematic control, this work provides evidence that the curvature is instead due to imperfect peripheral execution.Dynamics: In order to determine the exact cause of path curvature, an anatomically-accurate, mathematical model of the wrist was developed, including recent measurements of passive wrist stiffness. Combining experimentally-measured kinematics from human subjects with the wrist model revealed that moderately-sized wrist rotations can be approximated by a very simple model with virtually no loss in accuracy.Interaction torques, for which the nervous system compensates in reaching movements, are present but negligible in wrist rotations.en_US
dc.description.abstract(cont) Rather, wrist rotation dynamics are dominated by stiffness, which was shown to be the likely cause of path curvature.Adaptation: When perturbed during reaching movements, humans adapt by straightening their paths, confirming that kinematics play a prominent role in planning reaching movements. We found that subjects consistently adapted to a conservative,velocity-dependent force field. Interestingly, this adaptation was more difficult to detect than in perturbation studies involving reaching movements. Taken together, these results suggest that wrist rotations are also primarily under kinematic control (albeit imperfect).en_US
dc.description.statementofresponsibilityby Steven K. Charles.en_US
dc.format.extent234 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectHarvard University--MIT Division of Health Sciences and Technology.en_US
dc.titleIt's all in the wrist : a quantitative characterization of human wrist controlen_US
dc.title.alternativeQuantitative characterization of human wrist controlen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technology
dc.identifier.oclc320757845en_US


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