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.