Motor learning in hemi-Parkinson using VR-manipulated sensory feedback.

Our combination of cutting edge technologies, insights gained from basic motor neuroscience in healthy subjects and well-known clinical treatments, hold promise for the pursuit of finding novel and more efficient rehabilitation schemes for patients suffering from hemiplegia.Implications for rehabilitationAssistive devices used in hospitals to support patients with hemiparesis require expensive equipment and trained personnel - constraining the amount of training that a given patient can receive. The setup we describe is simple and can be easily used at home with the assistance of an untrained caregiver/family member. Once installed at the patient's home, the setup is lightweight, mobile, and can be used with minimal maintenance . Building on advances in machine learning, our software can be adapted to personal use at homes. Our findings can be translated into practice with relatively few adjustments, and our experimental design may be used as an important adjuvant to standard clinical care for upper limb hemiparesis.