Evaluation of similarities between robotic tasks for reduction of stroke assessment time

Robotic technologies provide accurate, objective, and highly reliable tools for assessment of brain function following stroke. KINARM is an exoskeleton device that uses a number of behavioral tasks to objectively quantify sensorimotor, proprioceptive and cognitive brain function using a battery of behavioral tasks. With a growing number of tasks deployed to more broadly assess different aspects of behavior on the KINARM system, different strategies are required to reduce the overall assessment time. Two specific tasks designed for assessment of visuomotor control, multi-joint coordination and cognitive processes related to attention and inhibition include Object Hit and Object Hit and Avoid tasks. The present study investigates the similarities between these two tasks using a system identification technique known as Fast Orthogonal Search. Results of our study show that all parameters of the Object Hit task can be predicted using Object Hit and Avoid parameters with R values ranging from 0.66 to 0.92, close to inter-rater reliability scores for the Object Hit parameters. We were able to classify stroke from control subjects using the predicted Object Hit task parameters, with similar accuracies as those obtained using the actual parameter values. These findings can be used to shorten the KINARM assessment procedure.

[1]  S. Scott,et al.  Potential of robots as next-generation technology for clinical assessment of neurological disorders and upper-limb therapy. , 2011, Journal of rehabilitation research and development.

[2]  S. Wolf,et al.  Exploring the bases for a mixed reality stroke rehabilitation system, Part I: A unified approach for representing action, quantitative evaluation, and interactive feedback , 2011, Journal of NeuroEngineering and Rehabilitation.

[3]  David Lee Gordon,et al.  Classification of Subtype of Acute Ischemic Stroke: Definitions for Use in a Multicenter Clinical Trial , 1993, Stroke.

[4]  Janice I. Glasgow,et al.  Assessment of Upper-Limb Sensorimotor Function of Subacute Stroke Patients Using Visually Guided Reaching , 2010, Neurorehabilitation and neural repair.

[5]  T. I. King Cognition and Perception in the Stroke Patient–A Guide to Functional Outcomes in Occupational Therapy , 1995 .

[6]  D. Corbett,et al.  Efficacy of Rehabilitative Experience Declines with Time after Focal Ischemic Brain Injury , 2004, The Journal of Neuroscience.

[7]  Ravi Vaidyanathan,et al.  2011 IEEE INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS (ICORR) , 2011 .

[8]  Stephen H Scott,et al.  Impaired corrective responses to postural perturbations of the arm in individuals with subacute stroke , 2015, Journal of NeuroEngineering and Rehabilitation.

[9]  Parvin Mousavi,et al.  Reduction of stroke assessment time for visually guided reaching task on KINARM exoskeleton robot , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  M. J. Korenberg,et al.  A robust orthogonal algorithm for system identification and time-series analysis , 1989, Biological Cybernetics.

[11]  Parvin Mousavi,et al.  Hierarchical task ordering for time reduction on KINARM assessment protocol , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[12]  S. Scott,et al.  Quantitative Assessment of Limb Position Sense Following Stroke , 2010, Neurorehabilitation and neural repair.

[13]  Pamela W. Duncan,et al.  Similar Motor Recovery of Upper and Lower Extremities After Stroke , 1994, Stroke.

[14]  Carl P. T. Jackson,et al.  A Novel Robotic Task for Assessing Impairments in Bimanual Coordination Post-Stroke , 2014 .

[15]  Jennifer A. Semrau,et al.  Robotic Identification of Kinesthetic Deficits After Stroke , 2013, Stroke.

[16]  Stephen H Scott,et al.  A robotic object hitting task to quantify sensorimotor impairments in participants with stroke , 2014, Journal of NeuroEngineering and Rehabilitation.

[17]  M. Korenberg,et al.  Orthogonal approaches to time-series analysis and system identification , 1991, IEEE Signal Processing Magazine.