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.
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 strokeparticipants 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 strokepatients 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.
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