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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Robotic motor training | Experimental | 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). |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Robotic motor training | Behavioral | The experiments consist in performing motor tasks with upper-limb robotic devices. |
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| 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) |
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Laura Marchal-Crespo, Prof. Dr. | University of Bern, ARTORG Center for Biomedical Engineering Research | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Bern | Bern | 3010 | Switzerland |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35152897 | Derived | Ozen O, Buetler KA, Marchal-Crespo L. Towards functional robotic training: motor learning of dynamic tasks is enhanced by haptic rendering but hampered by arm weight support. J Neuroeng Rehabil. 2022 Feb 13;19(1):19. doi: 10.1186/s12984-022-00993-w. |
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All individual participant data that underlie results in a publication
Data will be available after publications and it will stay accessible as long as the journal regulation permits.
Being able to access the journal paper
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| ID | Term |
|---|---|
| D020521 | Stroke |
| D009422 | Nervous System Diseases |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D014652 | Vascular Diseases |
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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 |
| D002318 | Cardiovascular Diseases |