Visual Feedback Reach Training for Ataxia

Overseen by Amy J Bastian, PhD, PT

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Hugo W. Moser Research Institute at Kennedy Krieger, Inc.

Disqualifiers: Dementia, Vision loss, others

No Placebo Group

Approved in 1 Jurisdiction

Trial Summary

What is the purpose of this trial?

This trial compares two training methods to improve arm movements in people with cerebellar ataxia. It targets individuals who struggle with movement coordination due to cerebellum damage. The methods involve practicing reaching movements with feedback to enhance coordination.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment Reach training with visual feedback for ataxia?

Research on similar treatments for stroke patients shows that visual feedback can help improve arm movement and balance. Studies found that visual feedback helps reduce unnecessary body movements and enhances performance, suggesting it could be beneficial for ataxia rehabilitation as well. ^{1 2 3 4 5}

Is visual feedback reach training safe for humans?

Research on visual feedback reach training, including studies with healthy participants and those with conditions like stroke, suggests it is generally safe. The studies did not report any adverse effects, and participants showed improvements in performance and reduced physical fatigue. ^{1 3 6 7 8}

How is the treatment 'Visual Feedback Reach Training for Ataxia' different from other treatments for ataxia?

This treatment is unique because it uses visual feedback to help patients improve their arm reaching movements, which can reduce unnecessary body movements and improve motor learning. Unlike other treatments that may rely on verbal feedback or robotic assistance, this approach focuses on visual cues, making it potentially less intimidating and more cost-effective. ^{2 3 6 8 9}

Research Team

Amy J Bastian, PhD, PT

Principal Investigator

Kennedy Krieger Institute and Johns Hopkins School of Medicine

Eligibility Criteria

This trial is for individuals aged 22-80 with cerebellar ataxia due to stroke, tumor, or degeneration. It's not suitable for those with extrapyramidal symptoms, vestibular loss, sensory neuropathy, significant pain or dementia (Mini-Mental State exam score > 22), vision loss affecting task performance, or damage to brain areas outside the cerebellum.

Inclusion Criteria

I am between 22 and 80 years old.

I have damage to my cerebellum due to stroke, tumor, or degeneration.

Exclusion Criteria

My vision loss affects my daily activities.

My pain stops me from doing daily tasks.

I have movement disorders, balance issues, or numbness in my limbs.

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants undergo reinforcement or standard practice training for reaching movements over a 12-week period

12 weeks

3 visits per week

Rest Period

Participants have a rest period between training phases

2 weeks

Follow-up

Participants are monitored for retention of training effects

2 weeks

2 visits

Treatment Details

Interventions

• Reach training with visual feedback (Behavioral Intervention)

Trial Overview The study tests a reinforcement-based training method against standard practices over several weeks to improve reaching movements in people with ataxia. Participants will receive reach training that includes visual feedback.

Participant Groups

Group I: Standard Practice Training Experimental Treatment 1 Intervention

Reach training with visual feedback. During each training session, participants will first be familiarized with the task and then will reach from a home position to 4 virtual targets that are presented in the front of the participant and within the workspace where most natural arm movements are performed. During training the participant will reach a total of 400 times. For standard practice, participants will be able to see a cursor that represents the position of the hand at all times and try to make straight reaches to the targets. This type of feedback provided specific information about the location of the hand.

Group II: Reinforcement Training Experimental Treatment 1 Intervention

Reach training with visual feedback. During each training session, participants will first be familiarized with the task and then will reach from a home position to 4 virtual targets that are presented in the front of the participant and within the workspace where most natural arm movements are performed. During training the participant will reach a total of 400 times. For reinforcement training, participants will not see their hand or a cursor, but instead participants will receive target-specific binary feedback after each reach (i.e. based on running average of last 10 reaches to that target). Binary feedback indicates only whether the reach was successful or unsuccessful and provides no specific information about the location of the hand.

Who Is Running the Clinical Trial?

Hugo W. Moser Research Institute at Kennedy Krieger, Inc.

Lead Sponsor

Trials

93

Recruited

25,200+

Dr. Bradley L. Schlaggar

Hugo W. Moser Research Institute at Kennedy Krieger, Inc.

Chief Executive Officer since 2018

MD/PhD from Washington University in St. Louis

Dr. Ali Fatemi

Hugo W. Moser Research Institute at Kennedy Krieger, Inc.

Chief Medical Officer since 2019

MD from Medical University of Vienna, MBA from Johns Hopkins Carey Business School

Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

Collaborator

Trials

2,103

Recruited

2,760,000+

Dr. Diana W. Bianchi

Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

Chief Executive Officer since 2016

MD from Stanford University

Dr. Alison Cernich

Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

Chief Medical Officer since 2020

PhD in Clinical Psychology from University of Maryland

National Institutes of Health (NIH)

Collaborator

Trials

2,896

Recruited

8,053,000+

Dr. Jeanne Marrazzo

National Institutes of Health (NIH)

Chief Medical Officer

MD from University of California, Los Angeles

Dr. Jay Bhattacharya

National Institutes of Health (NIH)

Chief Executive Officer

MD, PhD from Stanford University

Findings from Research

A randomized controlled trial involving subjects training in a virtual environment showed that both groups improved in motor recovery after three weeks of training, suggesting that rehabilitation can continue to be effective even after a plateau is reached.

The group using Error-Augmentation (EA) demonstrated consistent advantages in improvement, indicating that visual feedback can enhance rehabilitation outcomes similarly to robotic-assisted therapies, while also introducing greater variability in performance between trials.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Upper Extremity Functional Rehabilitation for Stroke Survivors Using Error-Augmented Visual Feedback: Interim Results. Porta, F., Celian, C., Patton, JL.[2021]

Visual feedback is more effective than verbal feedback in reducing trunk compensation during one-arm reaching exercises, as shown by decreased trunk movements in stroke survivors using an end-effector robot.

The study indicates that synchronized visual feedback can significantly improve trunk stability during rehabilitation, but it is limited by a small sample size, suggesting the need for further research in diverse patient groups and exercise types.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Effectiveness of Visual Feedback in Reducing Trunk Compensation During Arm Reaching for Home-Based Stroke Rehabilitation. Lee, SH., Song, WK.[2023]

Robotic therapy combined with visual feedback distortion can enhance rehabilitation for individuals with chronic stroke or traumatic brain injury by encouraging them to exceed their perceived performance limits.

In a six-week study involving two patients, both showed functional improvements, suggesting that this method can effectively help patients overcome learned nonuse and improve rehabilitation outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Visual feedback distortion in a robotic environment for hand rehabilitation. Brewer, BR., Klatzky, R., Matsuoka, Y.[2016]

In a study involving 21 subjects with simulated ultra-low vision and 3 patients with advanced retinitis pigmentosa, it was found that reaching movements were systematically inaccurate, with deviations primarily downward and towards the dominant hand.

Auditory feedback training significantly improved the accuracy of reaching movements, reducing deviations after 100 trials, suggesting it could be an effective tool for helping individuals with very low vision correct their orientation when reaching for targets.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

False reaching movements in localization test and effect of auditory feedback in simulated ultra-low vision subjects and patients with retinitis pigmentosa. Endo, T., Kanda, H., Hirota, M., et al.[2022]

In a study involving 20 stroke patients, visual feedback training significantly improved static and dynamic balance compared to unstable surface training after 4 weeks of intervention.

Both training methods enhanced balance parameters, but visual feedback training was more effective in reducing postural sway and improving stability limits, indicating its potential as a superior rehabilitation strategy for stroke patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Comparison of the effects of visual feedback training and unstable surface training on static and dynamic balance in patients with stroke. Hwang, HS., Kim, JH., Choi, BR.[2020]

Using a visual feedback-equipped reacher significantly reduced muscle activity in the flexor digitorum superficialis and extensor digitorum muscles during reach-to-grasp tasks, indicating less physical strain on the users.

The study, involving 17 healthy participants, also found that wrist momentum decreased when using the reacher with visual feedback, suggesting that this assistive device can help reduce physical fatigue and improve energy efficiency during tasks.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Use of a visual feedback-equipped reacher in reach-to-grasp movements. Do, JH., Yoo, WG.[2020]

Nonvisual feedback methods, particularly vibrotactile feedback, significantly improved movement correction in physical exercise, with a 11.2% increase in accuracy compared to no feedback, based on a study with 22 participants with normal vision.

Pilot testing with participants with impaired vision indicated that vibrotactile and multimodal feedback were also effective, suggesting these methods could enhance exercise performance and safety for individuals with vision impairment.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Effects of vibrotactile feedback on yoga practice. Islam, MS., Lee, SW., Harden, SM., et al.[2022]

A new visual distortion training method for stroke survivors, which simulates robot-assisted feedback without the actual robot, showed promising early results in improving motor skills during a bimanual virtual reality task.

Both treatment and control groups improved after three weeks of practice, with the treatment group showing a slight advantage, suggesting that visual feedback alone can be an effective and simpler alternative for rehabilitation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Stroke Rehabilitation with Distorted Vision Perceived as Forces. Hajissa, E., Celian, C., Thielbar, KO., et al.[2020]

In a study involving 30 healthy participants, those who received online visual feedback (VFb) during a reaching task showed faster learning and greater accuracy compared to those who did not receive visual feedback (NoVFb).

While both groups adapted to the task, the NoVFb group demonstrated slower learning and used less effective strategies, particularly when reaching for more challenging targets, indicating that visual feedback plays a crucial role in optimizing motor learning.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Impact of online visual feedback on motor acquisition and retention when learning to reach in a force field. Batcho, CS., Gagné, M., Bouyer, LJ., et al.[2017]

References

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

Upper Extremity Functional Rehabilitation for Stroke Survivors Using Error-Augmented Visual Feedback: Interim Results. [2021]

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

Effectiveness of Visual Feedback in Reducing Trunk Compensation During Arm Reaching for Home-Based Stroke Rehabilitation. [2023]

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

Visual feedback distortion in a robotic environment for hand rehabilitation. [2016]

4. Germany pubmed.ncbi.nlm.nih.gov

False reaching movements in localization test and effect of auditory feedback in simulated ultra-low vision subjects and patients with retinitis pigmentosa. [2022]

5. Japan pubmed.ncbi.nlm.nih.gov

Comparison of the effects of visual feedback training and unstable surface training on static and dynamic balance in patients with stroke. [2020]

6. Japan pubmed.ncbi.nlm.nih.gov

Use of a visual feedback-equipped reacher in reach-to-grasp movements. [2020]

7. Switzerland pubmed.ncbi.nlm.nih.gov

Effects of vibrotactile feedback on yoga practice. [2022]

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

Stroke Rehabilitation with Distorted Vision Perceived as Forces. [2020]

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

Impact of online visual feedback on motor acquisition and retention when learning to reach in a force field. [2017]