Robot-aided assessment of wrist proprioception.
BACKGROUND
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.


OBJECTIVE
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.


METHODS
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 r T2-T1 = 0.986 and r T3-T2 = 0.971.


CONCLUSIONS
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.
Department of Robotics Brain and Cognitive Sciences, Istituto Italiano di Tecnologia , Genova , Italy.
Leonardo
L
Cappello
School of Kinesiology, University of Minnesota , Minneapolis, MN , USA.
Naveen
N
Elangovan
School of Mechanical and Aerospace Engineering, Nanyang Technological University , Singapore , Singapore.
Sara
S
Contu
School of Kinesiology, University of Minnesota , Minneapolis, MN , USA.
Sanaz
S
Khosravani
School of Kinesiology, University of Minnesota , Minneapolis, MN , USA.
Jürgen
J
Konczak
School of Mechanical and Aerospace Engineering, Nanyang Technological University , Singapore , Singapore.
Lorenzo
L
Masia
discrimination threshold; quantitative measurements; robotic rehabilitation; wrist proprioception; wrist robot