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Description
Millions of Americans live with motor impairments resulting from a stroke and the best way to administer rehabilitative therapy to achieve recovery is not well understood. Adaptive mixed reality rehabilitation (AMRR) is a novel integration of motion capture technology and high-level media computing that provides precise kinematic measurements and engaging multimodal feedback for self-assessment during a therapeutic task. The AMRR system was evaluated in a small (N=3) cohort of stroke survivors to determine best practices for administering adaptive, media-based therapy. A proof of concept study followed, examining changes in clinical scale and kinematic performances among a group of stroke survivors who received either a month of AMRR therapy (N = 11) or matched dosing of traditional repetitive task therapy (N = 10). Both groups demonstrated statistically significant improvements in Wolf Motor Function Test and upper-extremity Fugl-Meyer Assessment scores, indicating increased function after the therapy. However, only participants who received AMRR therapy showed a consistent improvement in their kinematic measurements, including those measured in the trained reaching task (reaching to grasp a cone) and in an untrained reaching task (reaching to push a lighted button). These results suggest that that the AMRR system can be used as a therapy tool to enhance both functionality and reaching kinematics that quantify movement quality. Additionally, the AMRR concepts are currently being transitioned to a home-based training application. An inexpensive, easy-to-use, toolkit of tangible objects has been developed to sense, assess and provide feedback on hand function during different functional activities. These objects have been shown to accurately and consistently track hand function in people with unimpaired movements and will be tested with stroke survivors in the future.
ContributorsDuff, Margaret Rose (Author) / Rikakis, Thanassis (Thesis advisor) / He, Jiping (Thesis advisor) / Herman, Richard (Committee member) / Kleim, Jeffrey (Committee member) / Santos, Veronica (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2012
Description
Motion capture using cost-effective sensing technology is challenging and the huge success of Microsoft Kinect has been attracting researchers to uncover the potential of using this technology into computer vision applications. In this thesis, an upper-body motion analysis in a home-based system for stroke rehabilitation using novel RGB-D camera - Kinect is presented. We address this problem by first conducting a systematic analysis of the usability of Kinect for motion analysis in stroke rehabilitation. Then a hybrid upper body tracking approach is proposed which combines off-the-shelf skeleton tracking with a novel depth-fused mean shift tracking method. We proposed several kinematic features reliably extracted from the proposed inexpensive and portable motion capture system and classifiers that correlate torso movement to clinical measures of unimpaired and impaired. Experiment results show that the proposed sensing and analysis works reliably on measuring torso movement quality and is promising for end-point tracking. The system is currently being deployed for large-scale evaluations.
ContributorsDu, Tingfang (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Rikakis, Thanassis (Committee member) / Arizona State University (Publisher)
Created2012
ContributorsCompitello, Michael (Director) / Mancuso, Simone (Director) / Bell, Brett (Performer) / Chapman, Pat (Performer) / Chen, Kemi (Performer) / Falkner, Benjamin (Performer) / Fox, Ethan (Performer) / Frye, Kaileigh (Performer) / Grahmann, Robert (Performer) / Kang, Justin (Performer) / Lugo, Jacob (Performer) / Pardee, Lola (Performer) / West, Corbin (Performer) / Contemporary Percussion Ensemble (Performer) / ASU Library. Music Library (Publisher)
Created2021-03-23
ContributorsMancuso, Simone (Performer) / Buck, Elizabeth (Performer) / ASU Library. Music Library (Publisher)
Created2018-08-26
ContributorsSmith, J. B., 1957- (Director) / Mancuso, Simone (Director) / Contemporary Percussion Ensemble (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-18
ContributorsMancuso, Simone (Director) / Arizona Contemporary Music Ensemble (Performer) / ASU Library. Music Library (Contributor)
Created2018-04-14
ContributorsBuringrud, Deanna (Performer) / Clements, Katrina (Performer) / Bennet, Joshua (Performer) / Rasmussen, Eric (Performer) / Price, Alex (Performer) / Stover, Chris (Performer) / Healey, Biddy (Performer) / Berry, David (Performer) / Hedquist, Ben (Performer) / McClintock, Matt (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-28
ContributorsRosenfeld, Albor (Performer) / Pagano, Caio, 1940- (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-03
ContributorsMoio, Dom (Performer) / Tilburg, Shaun (Performer) / Smith, J. B., 1957- (Performer) / Mancuso, Simone (Performer) / Russo, Sam (Performer) / Sample, Connor (Performer) / Spring, Robert (Performer) / Tipei, Filip (Performer) / Wilson, Viviana Cumplido (Performer) / ASU Library. Music Library (Publisher)
Created2018-02-04
ContributorsSmith, J. B., 1957- (Director) / Mancuso, Simone (Director) / Contemporary Percussion Ensemble (Performer) / ASU Library. Music Library (Contributor)
Created2017-11-19