Clinical trial NCT04759976: Optimize Motor Learning to Improve Neurorehabilitation
Official title: Optimize Motor Learning to Improve Neurorehabilitation
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Stroke
Neurologic Disorder
Keywords: Neurorehabilitation
Robotic Rehabilitation
Motor Learning
Lead sponsor: University of Bern
Sponsor class: OTHER
First posted: 2021-02-18
Enrollment: 250
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: BASIC_SCIENCE

Brief summary: 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: 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.

Eligibility criteria: 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

Primary outcomes:
measure: Change in kinematic performance assessed by the robot
timeFrame: Baseline, training (immediately after baseline), retention (1-2 days after the training)
measure: Change in kinetic performance assessed by the robot
timeFrame: Baseline, training (immediately after baseline), retention (1-2 days after the training)
measure: Spatial analysis of changes in evoked potentials as assessed by Electroencephalography (EEG) measurement
timeFrame: Baseline, training (immediately after baseline), retention (1-2 days after the training)
Secondary outcomes:
measure: Change in embodiment
timeFrame: Before Intervention, Immediately after the end of intervention
measure: Spatial analysis of changes in Task-Based Brain Connectivity as assessed by Electroencephalography (EEG) measurement
timeFrame: Baseline, training (immediately after baseline or 1-2 days after baseline), retention (1-2 days after the training)
measure: Change in Motivation as assessed by Intrinsic Motivation Inventory (IMI)
timeFrame: Before Intervention, Immediately after the end of intervention, at the end of the session
measure: Change in Cognitive Load as assessed by National Aeronautics and Space Administration (NASA) (Raw) Task Load Index
timeFrame: Immediately after the end of intervention, At the end of the session
measure: System Usability as assessed by System Usability Scale (SUS)
timeFrame: Immediately after the end of intervention, At the end of the session
Other outcomes:
Locations:
city: Bern
country: Switzerland
facility: University of Bern
Study officials:
affiliation: University of Bern, ARTORG Center for Biomedical Engineering Research
name: Laura Marchal-Crespo, Prof. Dr.
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.