Evidence suggests that humans tune their motor behavior in response to environmental uncertainty. Such risk-aware sensorimotor performance is hypothetically affected in stroke due to impaired sensorimotor control, but its existence and the detailed pattern of impairment remain unclear - particularly due to lack of approaches for measurement of dynamic performance in stroke. Here we present the design and implementation of a platform for testing the upper-limb control in presence of motor uncertainty. The platform monitors how a patient with stroke, exclusively with the affected arm, navigates a virtual car by adjusting the hand position. We focus on how the control behavior changes when the car is perturbed with progressively larger Gaussian noise. Using this platform, we successfully collected data from 4 healthy subjects and 4 patients with post-stroke hemiparesis. Initial evidence suggests that patients with stroke failed to tune their performance with increasing level of Gaussian perturbation. The results imply that the risk-aware behavior potentially provides a new modality of biofeedback useful in therapeutic interventions.
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