title: Evaluation of upper extremity reachable workspace using Kinect camera.
abstract: BACKGROUND
  In clinical evaluation of upper extremity, there is a lack of assessment methods that are quantitative, reliable, and informative of the overall functional capability of an individual.
  
  
  OBJECTIVE
  We present new methodology for the assessment of upper extremity impairments based on the concept of 3-dimensional reachable workspace using Microsoft Kinect.
  
  
  METHODS
  We quantify the reachable workspace by the relative surface area representing the portion of the unit hemi-sphere that is covered by the hand movement. We examine accuracy of joint positions, joint angles, and reachable workspace computation between the Kinect and motion capture system.
  
  
  RESULTS
  The results of our analysis in 10 healthy subjects showed that the accuracy of the joint positions was within 66.3 mm for our experimental protocol. We found that the dynamic angle measurements had relatively large deviations (between 9° to 28°). The acquired reachable workspace envelope showed high agreement between the two systems with high repeatability between trials (correlation coefficients between 0.86 and 0.93).
  
  
  CONCLUSIONS
  The findings indicate that the proposed Kinect-based 3D reachable workspace analysis provides sufficiently accurate and reliable results as compared to motion capture system. The proposed method could be promising for clinical evaluation of upper extremity in neurological or musculoskeletal conditions.
authors.affiliation: Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA, USA Department of Physical Medicine and Rehabilitation, University of California at Davis Medical Center, Sacramento, CA, USA.
authors.forename: Gregorij
authors.initials: G
authors.lastname: Kurillo
authors.affiliation: Department of Mechanical Engineering, University of California at Berkeley, Berkeley, CA, USA.
authors.forename: Alic
authors.initials: A
authors.lastname: Chen
authors.affiliation: Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA, USA.
authors.forename: Ruzena
authors.initials: R
authors.lastname: Bajcsy
authors.affiliation: Department of Physical Medicine and Rehabilitation, University of California at Davis Medical Center, Sacramento, CA, USA.
authors.forename: Jay J
authors.initials: JJ
authors.lastname: Han
mesh_terms: D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010781:Photography / Q000295:instrumentation* / Q000379:methods; D016059:Range of Motion, Articular / Q000502:physiology*; D058998:Remote Sensing Technology / Q000295:instrumentation* / Q000379:methods; D034941:Upper Extremity / Q000502:physiology / Q000503:physiopathology*
keywords: Kinect; functional evaluation; reachable workspace; upper extremity