The investigators hypothesize that a myoelectric (EMG) controlled virtual reality (VR) interface allows for effective upper limb motor recovery of stroke patients. EMG control offers the possibility to alter visual feedback according to the recorded muscle activity in real-time. By manipulating the motion of a virtual hand associated with the recorded muscle patterns, assistance can be provided to stroke patients by correcting the error between the actual (dysfunctional) and a reference (functional) muscle pattern. Thus, through such an assistive EMG control algorithm, patients will be able to perform reaching movements with the virtual hand despite their motor impairment. By gradually reducing assistance, it is hypothesized that the salient error in the task space provided as visual feedback will systematically change the muscle patterns, thereby driving adaptation of the dysfunctional muscle patterns, enhancing motor recovery. Moreover, due to its relevant role in motor learning, it is expected that cerebellar stimulation will favor the underlying processes of adapting cerebello-cortical plasticity involved in motor learning. Therefore, it is hypothesized that an assistive EMG control algorithm in combination with cerebellar transcranial magnetic stimulation will further enhance upper limb recovery.
First ever ischemic stroke with mild to moderate motor impairment of upper limb;
Left or right sub-cortical or cortical lesion of the middle cerebral artery;
Age>18, <80 years;
No visuospatial, cognitive, or attention deficits;
History of seizures;
Treatment with Benzodiazepines, Baclofen;
Pregnancy status;
Intracranial metal implant;
Parallel
Virtual Reality Interface + Cerebellar iTBS (c-iTBS)
DeviceSubjects will sit in a chair with their forearm inserted in a splint attached to a force transducer. The subjects' view of their hand will be occluded by a mirror displaying the virtual scene. EMGs from arm and shoulder muscles will be recorded by surface EMG electrodes. Subjects will displace a virtual handle according to either the forces recorded by the force transducer or forces estimated from the recorded EMGs (EMG control).
Virtual Reality + Sham Cerebellar iTBS (sham c-iTBS)
Devicec-iTBS will be carried out using Magstim Rapid magnetic biphasic stimulator. Twenty 2-s trains of three-pulse bursts at 50 Hz repeated every 200 ms with an inter-train interval of 10 s, for a total of 190 s will be applied over the contralesional lateral cerebellum. The coil will be positioned tangentially to the scalp for real and 90° angled for sham c-iTBS.
Physical Therapy
Other interventionPassive mobilization and motor recruitment of impaired upper limb will be performed with the support of a physical therapist specialized in neurological rehabilitation.
Change in the Fugl-Meyer Assessment Scale for Upper Extremity (FMA-UE)
Comprehensive clinical measurement tool of upper limb functions after stroke. Range score form 0 to 66 points, a higher score represents an improvement.
Change in the Box and Block test (BBT)
BBT assesses the patient's manual dexterity. It is composed of a wooden box divided into two compartments by a partition and 150 blocks. The BBT administration consists of asking the client to move, one by one, the maximum number of blocks from one compartment of the box to the other of equal size within 60 seconds. The test is performed with both upper limbs separately to evaluate the manual dexterity of each arm individually.
Change in modified Barthel Index (mBI) score
mBI is an ordinal scale that measures functional independence in the domains of personal care and mobility. Score range is from 0 (totally dependent) to 100 (independent).
Change in the Nine Hole Peg Test (NHPT)
NHPT assesses the patient's fine manual dexterity and hand-eye coordination. It consists of a small board with nine holes and nine pegs. During the test, the patient is asked to place the pegs into the holes one by one and then remove them as quickly as possible. The total time to complete the task is recorded. The test is performed separately with each upper limb to evaluate the dexterity of both hands individually.
Change in muscle activation patterns (EMG)
Task performance in the EMG-control mode will be quantified by the initial angle error and the fraction of unsuccessful trials during the task execution. To combine the initial angle error and the fraction of unsuccessful trials into a single performance index, a linear combination approach will be used. We will compare the initial, baseline performance measure of EMG index of the first session with the performance of the last session.
Click on the lead sponsor to view all of their trials.