Optimize Motor Learning to Improve Neurorehabilitation

Study Overview
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Brief Summary
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The objective of this study is to develop and evaluate novel robotic training strategies that modulate errors based on the subjects' individual motor and cognitive needs. For this purpose, healthy adults and neurologic patients will participate in robotic motor learning experiments. Patients have a diagnosis of a neurological disease (i.e., stroke, spinal cord injury, multiple sclerosis, Guillain-Barré syndrome) limiting arm motor function.

Detailed Description
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Neurological patients (e.g., after stroke) engage in intensive and expensive neurorehabilitation therapy to regain part of their former motor functional ability to perform everyday activities with often limited and unsatisfactory outcome. Robots became a promising supplement or even alternative for neurorehabilitation therapy, providing cost-effective, high repetition and task-oriented training. However, results of an initial body of work comparing the effectiveness of robotic training strategies are highly inconclusive. A possible explanation is that most current robotic systems cover only one neurorehabilitation strategy (e.g. reducing or augmenting movement errors) and may thus insufficiently address the subjects' individual needs and the characteristics of the task to be learned. In this study, Investigators will perform several motor learning experiments with healthy adult and neurological patients in order to evaluate the relative motor and cognitive benefits of newly developed robotic training strategies that modulate errors based on the subject's age, skill level and tasks characteristics. The effects of the new strategies will be compared to classical robotic assistance, and to non-robotic feedback approaches, such as visual feedback. The culmination of this work may help to optimize training benefits of already existing rehabilitation robots.

Official Title
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Optimize Motor Learning to Improve Neurorehabilitation

Conditions
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Stroke, Neurologic Disorder

Intervention / Treatment
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* Behavioral: Robotic motor training


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Aged ≥18 years Informed Consent as documented by signature (Informed Consent form) Bodyweight <120 kg Ability to communicate effectively with the examiner so that the validity of the patient's data could not be compromised Exclusion Criteria: Excessive spasticity of the affected arm (Ashworth Scale ≥3) Serious medical or psychiatric disorder Orthopaedic, rheumatological, or other disease restricting movements of the paretic arm Shoulder subluxation Skin ulcerations at the paretic arm Cyber-sickness (i.e., nausea when looking at a screen or playing computer games) Serious cognitive defects or aphasia preventing effective use of the robotic devices Severe visual and auditory impairments

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Basic Science
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Robotic motor training<br>Participants will perform motor tasks (i.e. movements) with upper limb robotic devices applying different strategies (e.g. supporting or challenging the subject, or being fully compliant). | Behavioral: Robotic motor training<br>* The experiments consist in performing motor tasks with upper-limb robotic devices.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change in kinematic performance assessed by the robot | Motion changes from baseline in the kinematic variables assessed by the robot and motion trackers during the motor learning task. The kinematic performance analysis consists of end-effector position in the x, y, and z-axis, in meters, and joint angles in degrees. | Baseline, training (immediately after baseline), retention (1-2 days after the training) | 
| Change in kinetic performance assessed by the robot | Force changes from baseline in the kinetic variables assessed by the robot using force sensors during the motor learning task. Kinetic performance analysis consists of interaction forces in x, y, and z-axis, in N and applied robot joint torques by the motors, in Nm. | Baseline, training (immediately after baseline), retention (1-2 days after the training) | 
| Spatial analysis of changes in evoked potentials as assessed by Electroencephalography (EEG) measurement | Electroencephalographical assessment of changes in evoked potentials i.e. the electrical activity of the brain in response to stimulation of specific sensory nerve pathways. | Baseline, training (immediately after baseline), retention (1-2 days after the training) | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change in embodiment | Virtual Reality (VR) Embodiment Scale, Self administered Likert scale of 1-7 (Strongly Disagree to Strongly Agree) | Before Intervention, Immediately after the end of intervention | 
| Spatial analysis of changes in Task-Based Brain Connectivity as assessed by Electroencephalography (EEG) measurement | Changes in Task-Based Brain Connectivity from baseline in electroencephalography measurement | Baseline, training (immediately after baseline or 1-2 days after baseline), retention (1-2 days after the training) | 
| Change in Motivation as assessed by Intrinsic Motivation Inventory (IMI) | Intrinsic Motivation Inventory, Self administered. Likert scale of 1-7 (1: not at all true - 4: somewhat true - 7: very true) | Before Intervention, Immediately after the end of intervention, at the end of the session | 
| Change in Cognitive Load as assessed by National Aeronautics and Space Administration (NASA) (Raw) Task Load Index | Self-reported cognitive load during a task, Self-administered National Aeronautics and Space Administration (Raw) Task Load Index (TLX), analog scale mapped from 0 to 100 (Endpoints: Low/High, Good/Poor) | Immediately after the end of intervention, At the end of the session | 
| System Usability as assessed by System Usability Scale (SUS) | Self reported system usability assessed by System Usability Scale (SUS) Likert scale of 1-5 (Strongly agree to Strongly disagree) | Immediately after the end of intervention, At the end of the session | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Neurorehabilitation, Robotic Rehabilitation, Motor Learning