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Robot-Aided Assessment of Wrist Proprioception

L. Cappello,Naveen Elangovan,S. Contu,S. Khosravani,J. Konczak,L. Masia

Published 2015 in Frontiers in Human Neuroscience

ABSTRACT

Introduction Impaired proprioception severely affects the control of gross and fine motor function. However, clinical assessment of proprioceptive deficits and its impact on motor function has been difficult to elucidate. Recent advances in haptic robotic interfaces designed for sensorimotor rehabilitation enabled the use of such devices for the assessment of proprioceptive function. Purpose This study evaluated the feasibility of a wrist robot system to determine proprioceptive discrimination thresholds for two different DoFs of the wrist. Specifically, we sought to accomplish three aims: first, to establish data validity; second, to show that the system is sensitive to detect small differences in acuity; third, to establish test–retest reliability over repeated testing. Methodology Eleven healthy adult subjects experienced two passive wrist movements and had to verbally indicate which movement had the larger amplitude. Based on a subject’s response data, a psychometric function was fitted and the wrist acuity threshold was established at the 75% correct response level. A subset of five subjects repeated the experimentation three times (T1, T2, and T3) to determine the test–retest reliability. Results Mean threshold for wrist flexion was 2.15°± 0.43° and 1.52°± 0.36° for abduction. Encoder resolutions were 0.0075°(flexion–extension) and 0.0032°(abduction–adduction). Motor resolutions were 0.2°(flexion–extension) and 0.3°(abduction–adduction). Reliability coefficients were rT2-T1 = 0.986 and rT3-T2 = 0.971. Conclusion We currently lack established norm data on the proprioceptive acuity of the wrist to establish direct validity. However, the magnitude of our reported thresholds is physiological, plausible, and well in line with available threshold data obtained at the elbow joint. Moreover, system has high resolution and is sensitive enough to detect small differences in acuity. Finally, the system produces reliable data over repeated testing.

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