Robotic Controllers for Motor Learning After Neurological Injuries

(HRCEML Trial)

Overseen By Jose Pons, Ph.D

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Shirley Ryan AbilityLab

Must not be taking: Botox

Disqualifiers: Pregnancy, Neurological diseases, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 40

764 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

The purpose of this study is to develop a new paradigm to understand how humans physically interact with each other at a single and at multiple joints, with multiple contact points, so as to synthesize robot controllers that can exhibit human-like behavior when interacting with humans (e.g., exoskeleton) or other co-robots. The investigators will develop models for a single joint robot (i.e. at the ankle joint) that can vary its haptic behavioral interactions at variable impedances, and replicate in a multi-joint robot (i.e. at the ankle, knee, and hip joints). The investigators will collect data from healthy participants and clinical populations to create a controller based on our models to implement in the robots. Then, the investigators will test our models via the robots to investigate the mechanisms underlying enhanced motor learning during different human-human haptic interaction behaviors (i.e. collaboration, competition, and cooperation. This study will be carried out in healthy participants, participants post-stroke, and participants with spinal cord injury (SCI).

Do I need to stop taking my current medications to join the trial?

The trial information does not specify whether you need to stop taking your current medications. However, it mentions that participants should not have concurrent medical treatments, which might imply some restrictions. It's best to discuss your specific medications with the trial coordinators.

Is the use of robotic controllers for motor learning after neurological injuries safe for humans?

Research suggests that robotic controllers, such as exoskeletons, are generally safe for use in rehabilitation, as they have been part of clinical practice for over a decade and are designed to ensure safe physical interaction with users. Preliminary studies, including those involving stroke patients, indicate that these systems are feasible and safe for use in rehabilitation settings. ^{1 2 3 4 5}

How does the robotic controller treatment for motor learning after neurological injuries differ from other treatments?

This treatment is unique because it uses robotic controllers that adapt to the patient's recovery stage, providing personalized, task-oriented rehabilitation. Unlike traditional therapies, it emphasizes 'assist-as-needed' support, encouraging patients to actively participate in their recovery by only providing help when necessary, which can enhance motor learning and functional restoration. ^{1 4 6 7 8}

What data supports the effectiveness of the treatment Human-like Robotic Controllers, Co-Robot Controllers, Exoskeleton-based Dyadic Interaction Infrastructure for motor learning after neurological injuries?

Research shows that robotic systems, including exoskeletons, can help with motor recovery by providing repetitive and task-oriented practice, which is important for relearning movements after neurological injuries. Studies suggest that these systems can be as effective as traditional therapy methods, promoting motor relearning and functional restoration. ^{1 4 7 9 10}

Who Is on the Research Team?

Jose Pons, Ph.D

Principal Investigator

Shirley Ryan AbilityLab

Are You a Good Fit for This Trial?

This trial is for individuals aged 18-80 with normal hearing and vision, who can understand English and give informed consent. It's suitable for healthy participants as well as those post-stroke or with spinal cord injury (SCI), provided they can walk over 10m independently. People with brain lesions, neurological disorders, abnormal limb movements, or outside the height range of 3'6" to 6'2" cannot join.

Inclusion Criteria

Height between 3 foot 6 inches (1.1 meters) and 6 foot 2 inches

I had a stroke more than 6 months ago.

I can walk more than 10 meters by myself, even with help from devices.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Experiment A

Recruitment of healthy volunteers to model human adaptation in dyadic interactions and develop robot controllers

12 weeks

10 sessions

Experiment B

Testing robot controllers with healthy volunteers, post-stroke, and SCI participants to assess mechanical adaptation and role sharing

5 months

20 sessions

Experiment C

Showcasing robot controllers with post-stroke and SCI participants to observe motor learning and functional outcomes

5 months

10 sessions per robot

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Human-like Robotic Controllers

Trial Overview The study aims to develop robot controllers that mimic human behavior in physical interactions. These will be tested on single joint (ankle) and multi-joint (ankle, knee, hip) robots using variable haptic behaviors like collaboration and competition to enhance motor learning in humans.

How Is the Trial Designed?

Group I: Healthy Participants Bilateral Lower Limb Exoskeleton (H3/X2) Experimental Treatment 3 Interventions

The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected.

Group II: Healthy Participants Ankle Robot (M1) Experimental Treatment 3 Interventions

The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected.

Group III: Clinical Populations Bilateral Lower Limb Exoskeleton (H3/X2) Experimental Treatment 4 Interventions

The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected.

Group IV: Clinical Populations Ankle Robot (M1) Experimental Treatment 4 Interventions

The investigators will look at how the task performance and motor performance of individuals in dyadic physical interactions are affected.

Who Is Running the Clinical Trial?

Shirley Ryan AbilityLab

Lead Sponsor

Trials

212

Recruited

17,900+

U.S. National Science Foundation

Collaborator

Trials

35

Recruited

9,000+

Published Research Related to This Trial

Robot-assisted rehabilitation therapy for neurological patients aims to enhance motor plasticity through repetitive and task-oriented training, with a focus on adapting to the patient's recovery stage.

The paper proposes a three-level classification system for developing effective upper-limb rehabilitation exoskeletons, emphasizing the importance of compliant control strategies that foster collaboration between the robot and the patient to improve rehabilitation outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Review on Patient-Cooperative Control Strategies for Upper-Limb Rehabilitation Exoskeletons. Dalla Gasperina, S., Roveda, L., Pedrocchi, A., et al.[2021]

Robotic systems for neuromotor rehabilitation have been used in clinical practice for over a decade, but their effectiveness remains uncertain due to a lack of consensus on key features and theoretical foundations for treatment protocols.

The authors propose a 'research pipeline' that includes validated models of neural control, motor learning, and functional recovery to improve the design of robotic therapies and facilitate better comparisons in clinical trials.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Robot therapy of the upper limb in stroke patients: preliminary experiences for the principle-based use of this technology. Casadio, M., Giannoni, P., Masia, L., et al.[2016]

A pilot study involving 9 healthy subjects and 2 stroke patients explored the use of a multi-joint exoskeleton for robotic assistance during motor imagery tasks, showing that proprioceptive feedback improved control and performance of the robotic movements.

The study suggests that brain-robot interfaces (BRIs) could enhance rehabilitation by linking robotic training to the user's brain activity, potentially allowing for personalized adjustments in task difficulty to aid motor learning and recovery in stroke patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Brain state-dependent robotic reaching movement with a multi-joint arm exoskeleton: combining brain-machine interfacing and robotic rehabilitation. Brauchle, D., Vukelić, M., Bauer, R., et al.[2020]

The study involving 46 subacute stroke patients demonstrated that overground exoskeleton-assisted gait training (OEAGT) significantly improved clinical and gait outcomes, with many patients regaining the ability to walk after treatment.

Patients reported a positive acceptance of the OEAGT, indicating its potential as an innovative rehabilitation strategy, although further randomized studies with larger samples are needed to confirm these findings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Overground wearable powered exoskeleton for gait training in subacute stroke subjects: clinical and gait assessments. Goffredo, M., Guanziroli, E., Pournajaf, S., et al.[2020]

In a study involving 27 chronic stroke patients, both robotic and non-robotic rehabilitation techniques led to similar improvements in movement ability, indicating that these methods may activate a common recovery mechanism.

The recovery process followed a similar exponential time course of about 4-5 weeks for both training techniques, suggesting that the effectiveness of rehabilitation may depend more on the engagement of the nervous system rather than the specific method used.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Do robotic and non-robotic arm movement training drive motor recovery after stroke by a common neural mechanism? Experimental evidence and a computational model. Reinkensmeyer, DJ., Maier, MA., Guigon, E., et al.[2020]

The Tele-REINVENT system, a low-cost telerehabilitation biofeedback tool, has been developed to help stroke survivors improve muscle control at home, showing feasibility and safety in a case study with one stroke patient over 40 sessions in 10 weeks.

Preliminary results indicate that the system can effectively train differentiated muscle activity and reduce unwanted co-contractions, suggesting it could be a valuable tool for personalized rehabilitation in chronic stroke patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development of a Low-Cost, Modular Muscle-Computer Interface for At-Home Telerehabilitation for Chronic Stroke. Marin-Pardo, O., Phanord, C., Donnelly, MR., et al.[2021]

Exoskeletons are advanced wearable robots designed to assist individuals with motor disorders, enhancing rehabilitation through close cognitive and physical interaction with users.

Key areas for future development include improving the safety and reliability of human-robot interactions, ensuring the exoskeletons are portable and user-friendly, and addressing user acceptance to maximize their effectiveness in rehabilitation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Rehabilitation exoskeletal robotics. The promise of an emerging field. Pons, JL.[2010]

Robotic rehabilitation technologies have not shown significantly better patient outcomes compared to traditional therapy, but they can reduce the physical workload for therapists during high-intensity interventions.

Involving therapists more directly in the control of robotic systems may enhance rehabilitation effectiveness by fostering better patient-therapist-robot interactions and promoting neuroplastic changes essential for recovery.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Neurorehabilitation robotics: how much control should therapists have? Hasson, CJ., Manczurowsky, J., Collins, EC., et al.[2023]

Healthy subjects successfully learned to control a cursor using shoulder and upper arm movements, demonstrating the potential for optimizing movement reorganization in individuals with neuromotor disorders.

With practice, participants improved their cursor control, achieving faster, smoother, and more precise movements, which suggests that similar training could enhance the effectiveness of assistive devices for disabled users.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Functional reorganization of upper-body movements for wheelchair control. Casadio, M., Pressman, A., Danziger, Z., et al.[2020]

A novel adaptive controller for robot-aided movement training after stroke was developed, featuring high mechanical compliance and the ability to provide only the necessary assistance to patients, enhancing their engagement in therapy.

Tests with the Pneu-WREX robotic device showed that the 'assist-as-needed' approach improved patient participation and demonstrated the natural tendency of patients to rely on the robot for support when they could, which helps in motor learning and rehabilitation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Optimizing compliant, model-based robotic assistance to promote neurorehabilitation. Wolbrecht, ET., Chan, V., Reinkensmeyer, DJ., et al.[2022]

Citations

1. Switzerland pubmed.ncbi.nlm.nih.gov

Review on Patient-Cooperative Control Strategies for Upper-Limb Rehabilitation Exoskeletons. [2021]

2. Italy pubmed.ncbi.nlm.nih.gov

Robot therapy of the upper limb in stroke patients: preliminary experiences for the principle-based use of this technology. [2016]

3. Switzerland pubmed.ncbi.nlm.nih.gov

Brain state-dependent robotic reaching movement with a multi-joint arm exoskeleton: combining brain-machine interfacing and robotic rehabilitation. [2020]

4. Italy pubmed.ncbi.nlm.nih.gov

Overground wearable powered exoskeleton for gait training in subacute stroke subjects: clinical and gait assessments. [2020]

5. United States pubmed.ncbi.nlm.nih.gov

Do robotic and non-robotic arm movement training drive motor recovery after stroke by a common neural mechanism? Experimental evidence and a computational model. [2020]

6. Switzerland pubmed.ncbi.nlm.nih.gov

Development of a Low-Cost, Modular Muscle-Computer Interface for At-Home Telerehabilitation for Chronic Stroke. [2021]

7. United States pubmed.ncbi.nlm.nih.gov

Rehabilitation exoskeletal robotics. The promise of an emerging field. [2010]

8. Switzerland pubmed.ncbi.nlm.nih.gov

Neurorehabilitation robotics: how much control should therapists have? [2023]

9. United States pubmed.ncbi.nlm.nih.gov

Functional reorganization of upper-body movements for wheelchair control. [2020]

10. United States pubmed.ncbi.nlm.nih.gov

Optimizing compliant, model-based robotic assistance to promote neurorehabilitation. [2022]