Author Profile

Ruzena Bajcsy

http://www.eecs.berkeley.edu/Faculty/Homepages/bajcsy.html

Institution: University of California at Berkeley

Department: Department of Electrical Engineering and Computer Sciences

City: Berkeley

State: California

Country: USA

I graduated from Computer Science department at Stanford University in 1972 with PhD degree. Then I spent 30 years at the University of Pennsylvania as a professor in Computer and Information Science department. In 2001 I joined the EECS department at UC Berkeley,CA. Over 40 years I have pursued research in Computer Vision, Robotics and Medical Imaging. I am a member of the NAE and IOM of the National Academy of Sciences.

Recent Posts

Validity, Reliability, and Sensitivity of a 3D Vision Sensor-based Upper Extremity Reachable Workspace Evaluation in Neuromuscular Diseases

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Introduction: One of the major challenges in the neuromuscular field has been lack of upper extremity outcome measures that can be useful for clinical therapeutic efficacy studies. Using vision-based sensor system and customized software, 3-dimensional (3D) upper extremity motion analysis can reconstruct a reachable workspace as a valid, reliable and sensitive outcome measure in various neuromuscular conditions where proximal upper extremity range of motion and function is impaired.

Methods: Using a stereo-camera sensor system, 3D reachable workspace envelope surface area normalized to an individual’s arm length (relative surface area: RSA) to allow comparison between subjects was determined for 20 healthy controls and 9 individuals with varying degrees of upper extremity dysfunction due to neuromuscular conditions. All study subjects were classified based on Brooke upper extremity function scale. Right and left upper extremity reachable workspaces were determined based on three repeated measures. The RSAs for each frontal hemi-sphere quadrant and total reachable workspaces were determined with and without loading condition (500 gram wrist weight). Data were analyzed for assessment of the developed system and validity, reliability, and sensitivity to change of the reachable workspace outcome.

Results: The mean total RSAs of the reachable workspace for the healthy controls and individuals with NMD were significantly different (0.586 ± 0.085 and 0.299 ± 0.198 respectively; p<0.001). All quadrant RSAs were reduced for individuals with NMDs compared to the healthy controls and these reductions correlated with reduced upper limb function as measured by Brooke grade. The upper quadrants of reachable workspace (above the shoulder level) demonstrated greatest reductions in RSA among subjects with progressive severity in upper extremity impairment. Evaluation of the developed outcomes system with the Bland-Altman method demonstrated narrow 95% limits of agreement (LOA) around zero indicating high reliability. In addition, the intraclass correlation coefficient (ICC) was 0.97. Comparison of the reachable workspace with and without loading condition (wrist weight) showed significantly greater RSA reduction in the NMD group than the control group (p<0.012), with most of the workspace reduction occurring in the ipsilateral upper quadrant relative to the tested arm (p<0.001). Reduction in reachable workspace due to wrist weight was most notable in those subjects with NMD with marginal strength reserve and moderate degree of impairment (Brooke = 2) rather than individuals with mild upper extremity impairment (Brooke = 1) or individuals who were more severely impaired (Brooke =3).

Discussion: The developed reachable workspace evaluation method using scalable 3D vision technology appears promising as an outcome measure system for clinical studies. A rationally-designed combination of upper extremity outcome measures including a region-specific global upper extremity outcome measure, such as the reachable workspace, complemented by targeted disease- or function-specific endpoints, may be optimal for future clinical efficacy trials.