A pilot study evaluating use of a computer-assisted neurorehabilitation platform for upper-extremity stroke assessment.
BACKGROUND
There is a need to develop cost-effective, sensitive stroke assessment instruments. One approach is examining kinematic measures derived from goal-directed tasks, which can potentially be sensitive to the subtle changes in the stroke rehabilitation process. This paper presents the findings from a pilot study that uses a computer-assisted neurorehabilitation platform, interfaced with a conventional force-reflecting joystick, to examine the assessment capability of the system by various types of goal-directed tasks.


METHODS
Both stroke subjects with hemiparesis and able-bodied subjects used the force-reflecting joystick to complete a suite of goal-directed tasks under various task settings. Kinematic metrics, developed for specific types of goal-directed tasks, were used to assess various aspects of upper-extremity motor performance across subjects.


RESULTS
A number of metrics based on kinematic performance were able to differentiate subjects with different impairment levels, with metrics associated with accuracy, steadiness and speed consistency showing the best capability. Significant differences were also shown on these metrics between various force field settings.


CONCLUSIONS
The results support the potential of using UniTherapy software with a conventional joystick system as an upper-extremity assessment instrument. We demonstrated the ability of using various types of goal-directed tasks to distinguish between subjects with different impairment levels. In addition, we were able to show that different force fields have a significant effect on the performance across subjects with different impairment levels in the trajectory tracking task. These results provide motivation for studies with a larger sample size that can more completely span the impairment space, and can use insights presented here to refine considerations of various task settings so as to generalize and extend our conclusions.
Feng
Xin
X
Marquette University, Dept of Biomedical Engineering, Olin Engineering Center, Milwaukee, Wisconsin 53233, USA. xinfeng@lexmark.com
Winters
Jack M
JM
D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D001132:Arm; D001696:Biomechanical Phenomena; D005260:Female; D006040:Goals; D006801:Humans; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D010291:Paresis / Q000175:diagnosis* / Q000209:etiology / Q000534:rehabilitation*; D010865:Pilot Projects; D011597:Psychomotor Performance; D012984:Software; D020521:Stroke / Q000150:complications / Q000175:diagnosis*; D000071939:Stroke Rehabilitation; D013647:Task Performance and Analysis