Show simple item record

dc.contributor.advisorNeville Hogan.en_US
dc.contributor.authorHermus, James Russellen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.date.accessioned2018-10-22T18:27:37Z
dc.date.available2018-10-22T18:27:37Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/118670
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.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.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 113-119).en_US
dc.description.abstractDespite large feedback delays, and many degrees of freedom, humans are incredibly dexterous and excel at physical interaction with complex objects. In this work we developed an upper limb crank turning experiment to study the human controller used to manage physical interaction. Subjects turned a crank with and without visual feedback, in two directions (clockwise and counterclockwise), and in three speed conditions (slow (0.075 rev/s), medium (0.5 rev/s), and fast (2 rev/s)). We made several predictions about the dependent measures including: mean speed, standard deviation of speed, coefficient of variation of speed, mean normal force, and standard deviation of normal force. We hypothesized that subjects should perform the best at slow speeds where the effect of feedback delays, inertial dynamics, and muscle noise decrease. Notably, subjects became more variable at slow speeds, and exerted significant nonzero normal force in the slow condition. At slow speeds, increased speed variability and compressive normal forces cannot be explained by biomechanics - suggesting they result from neural control. Next, the zero-force trajectory was computed. The zero-force trajectory allows for the peripheral biomechanics to be 'subtracted' to 'reveal' the underlying neural commands, expressed in terms of motion. We detected a coincidence of curvature and velocity extrema in the zero-force trajectory. Furthermore, this observation was robust to changes in impedance parameters. This finding is exciting. Even though the hand was confined to a circular path, when the peripheral biomechanics were subtracted, the same velocity curvature relationship seen in unconstrained movements was revealed. Lastly, the increased variability at slow speeds was present in the zero force trajectory. This indicates that the increased variability at slow speeds is a result of neural control, not biomechanics; this finding is consistent with previous research in unconstrained motion.en_US
dc.description.sponsorshipNational Science Foundation National Robotics Initiative Grant No. 1637824en_US
dc.description.statementofresponsibilityby James Russell Hermus.en_US
dc.format.extent119 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.titleHuman physical interaction with a circular constrainten_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.identifier.oclc1057343221en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record