title: Test-retest reliability of Kinect's measurements for the evaluation of upper body recovery of stroke patients.
abstract: BACKGROUND
  Performance indices provide quantitative measures for the quality of motion, and therefore, assist in analyzing and monitoring patients' progress. Measurement of performance indices requires costly devices, such as motion capture systems. Recent developments of sensors for game controllers, such as Microsoft Kinect, have motivated many researchers to develop affordable systems for performance measurement applicable to home and clinical care. In this work, the capability of Kinect in finding motion performance indices was assessed by analyzing intra-session and inter-session test-retest reliability.
  
  
  METHODS
  Eighteen stroke patients and twelve healthy subjects participated in this investigation. The intra-session and inter-session reliability of eight performance indices, namely mean velocity (MV), normalized mean speed (NMS), normalized speed peaks (NSP), logarithm of dimensionless jerk (LJ), curvature (C), spectral arc length (SAL), shoulder angle (SA), and elbow angle (EA), were assessed using intra-class correlation coefficient (ICC), standard error of measurement (SEM) and coefficient of variation (CV).
  
  
  RESULTS
  The results showed that, among the performance indices, MV, LJ, C, SA and EA have more than 0.9 ICC together with an acceptable SEM and CV in both stroke patients and healthy subjects. Comparing the results of different therapy sessions showed that MV, LJ and C are more sensitive than other indices, and hence, more capable of reflecting the progress of a patient during the rehabilitation process.
  
  
  CONCLUSIONS
  The results of this study shows acceptable reliability and sensitivity across the sessions for MV, LJ and C measured by Kinect for both healthy subjects and stroke patients. The results are promising for the development of home-based rehabilitation systems, which can analyze patient's movements using Kinect as an affordable motion capture sensor.
authors.affiliation: Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran. amobini@mech.sharif.edu.
authors.forename: A
authors.initials: A
authors.lastname: Mobini
authors.affiliation: Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran. behzadipour@sharif.edu.
authors.forename: S
authors.initials: S
authors.lastname: Behzadipour
authors.affiliation: Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran. m_saadat@sharif.edu.
authors.forename: M
authors.initials: M
authors.lastname: Saadat
mesh_terms: D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009068:Movement; D020127:Recovery of Function; D015203:Reproducibility of Results; D020521:Stroke / Q000503:physiopathology*; D000071939:Stroke Rehabilitation; D018910:Video Games