Gross Motor AbiLity predictS Response to upper extremity rehabilitation in chronic stroke.

Gross Motor AbiLity predictS Response to upper extremity rehabilitation in chronic stroke. Behav Brain Res. 2017 Jul 05;: Authors: George SH, Rafiei MH, Borstad A, Adeli H, Gauthier LV Abstract The majority of rehabilitation research focuses on the comparative effectiveness of different interventions in groups of patients, while much less is currently known regarding individual factors that predict response to rehabilitation. In a recent article, authors presented a prognostic model to identify the sensorimotor characteristics predictive of the extent of motor recovery after Constraint-Induced Movement (CI) therapy amongst individuals with chronic mild-to-moderate motor deficit using the enhanced probabilistic neural network (EPNN). This follow-up paper examines which participant characteristics are robust predictors of rehabilitation response irrespective of the training modality. To accomplish this, EPNN was first applied to predict treatment response amongst individuals who received a virtual-reality gaming intervention (utilizing the same enrollment criteria as the prior study). The combinations of predictors that yield high predictive validity for both therapies, using their respective datasets, were then identified. High predictive classification accuracy was achieved for both the gaming (94.7%) and combined datasets (94.5%). Though CI therapy employed primarily fine-motor training tasks and the gaming intervention emphasized g...
Source: Behavioural Brain Research - Category: Neurology Authors: Tags: Behav Brain Res Source Type: research