Assessment of upper-limb sensorimotor function of subacute stroke patients using visually guided reaching.

OBJECTIVE: Using robotic technology, we examined the ability of a visually guided reaching task to assess the sensorimotor function of patients with stroke. METHODS: Ninety-one healthy participants and 52 with subacute stroke of mild to moderate severity (26 with left- and 26 with right-affected body sides) performed an unassisted reaching task using the KINARM robot. Each participant was assessed using 12 movement parameters that were grouped into 5 attributes of sensorimotor control. RESULTS: A number of movement parameters individually identified a large number of stroke participants as being different from 95% of the controls-most notably initial direction error, which identified 81% of left-affected patients. We also found interlimb differences in performance between the arms of those with stroke compared with controls. For example, whereas only 31% of left-affected participants showed differences in reaction time with their affected arm, 54% showed abnormal interlimb differences in reaction time. Good interrater reliability (r > 0.7) was observed for 9 of the 12 movement parameters. Finally, many stroke patients deemed impaired on the reaching task had been scored 6 or less on the arm portion of the Chedoke-McMaster Stroke Assessment Scale, but some who scored a normal 7 were also deemed impaired in reaching. CONCLUSIONS: Robotic technology using a visually guided reaching task can provide reliable information with greater sensitivity about a patient's sensorimotor impairments following stroke than a standard clinical assessment scale.

Quantitative assessment of limb position sense following stroke.

BACKGROUND: Impairment of position sense of the upper extremity (UE) may impede activities of daily living and limit motor gains after stroke. Most clinical assessments of position sense rely on categorical or ordinal ratings by clinicians that lack sensitivity to change or the ability to discriminate subtle deficits. OBJECTIVE: Use robotic technology to develop a reliable, quantitative technique with a continuous scale to assess UE position sense following stroke. METHODS: Forty-five patients recruited from an inpatient stroke rehabilitation service and 65 age-matched healthy controls performed an arm position matching task. Each UE was fitted in the exoskeleton of a KINARM device. One UE was passively placed in one of 9 positions, and the subject was told to match his or her position with the other UE. Patients were compared with statistical distributions of control data to identify those with deficits in UE position sense. Test-retest sessions using 2 raters established interrater reliability. RESULTS: Two thirds of left hemiparetic and one third of right hemiparetic patients had deficits in limb position sense. Left-affected stroke subjects demonstrated significantly more trial-to-trial variability than right-affected or control subjects. The robotic assessment technique demonstrated good interrater reliability but limited agreement with the clinical thumb localizing test. CONCLUSIONS: Robotic technology can provide a reliable quantitative means to assess deficits in limb position sense following stroke.