MyoTrain for Upper Extremity Amputation

Overseen By Rahul R Kaliki

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Infinite Biomedical Technologies

Disqualifiers: Unhealed wounds, Cognitive deficits, others

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

Approved in 1 Jurisdiction This treatment is already approved in other countries

Compensation: Varies

Number of Visits: 4

16 Participants Needed

Trial Summary

What is the purpose of this trial?

The investigators propose to evaluate the efficacy of MyoTrain in a prospective clinical study involving 16 individuals with trans-radial upper-limb loss over a period of 206 days. These individuals will be randomized to Group A (Control Group using standard motor imagery training) and Group B (who are provided the MyoTrain system). The investigators will test three hypotheses: 1. The use of MyoTrain results in skills transference to control of the final prosthesis 2. The virtual outcome measures in MyoTrain are correlated with real-world functional outcome measures 3. The use of MyoTrain results in improved clinical outcomes as measured by functional, subjective and usage metrics Following a baseline functional assessment, participants will undergo a 30-day pre-prosthetic training period specific to their assigned Group. After this training period, participants will receive their prosthetic device and occupational therapy consistent with the current clinical care standard, after which they will again undergo clinical assessment. Post-device delivery, participants will then complete 3 56-day blocks of at-home prosthesis use, in between which they will return to clinic for assessment.

Do I need to stop my current medications for the MyoTrain trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment MyoTrain for Upper Extremity Amputation?

Research shows that virtual reality training platforms can effectively teach people with upper limb loss to control advanced prosthetic limbs, improving their ability to perform complex motions. This suggests that MyoTrain, which uses a virtual-limb training system, may help individuals learn to use their prostheses more effectively. ^{1 2 3 4 5}

Is MyoTrain safe for human use?

The studies reviewed do not report any specific safety concerns related to MyoTrain or similar training systems for myoelectric prostheses. Participants in these studies generally found the training methods comfortable and usable, suggesting they are safe for human use. ^{1 5 6 7 8}

How is the MyoTrain treatment different from other treatments for upper extremity amputation?

MyoTrain is unique because it uses a virtual reality system to train individuals with upper extremity amputations to control advanced prosthetic limbs, allowing them to practice muscle movements and control schemes in a simulated environment before receiving their prosthesis. This approach is more engaging and can be done at home, making it different from traditional training methods that often require in-person sessions with a therapist. ^{1 9 10 11 12}

Eligibility Criteria

This trial is for adults over 18 who have lost a limb at the forearm level, are fluent in English, and qualify for an advanced myoelectric prosthesis. It's not suitable for those with other types of limb loss or conditions that would exclude them from using this technology.

Inclusion Criteria

Candidate for a 2+ degree-of-freedom myoelectric pattern recognition prosthesis as determined by prosthetist

Fluent in English

I have lost one arm.

Exclusion Criteria

Prior experience with pattern recognition control

Patients with easily damaged or sensitive skin who would not tolerate EMG electrodes

Significant cognitive deficits as determined upon clinical evaluation

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Baseline Assessment

Participants undergo a baseline functional assessment before starting the training period

1 day

Pre-prosthetic Training

Participants undergo a 30-day pre-prosthetic training period specific to their assigned group

4 weeks

1 visit (in-person)

Prosthetic Device Delivery and Occupational Therapy

Participants receive their prosthetic device and occupational therapy consistent with the current clinical care standard

1-2 weeks

At-home Prosthesis Use

Participants complete 3 blocks of 56-day at-home prosthesis use, with clinic assessments in between

24 weeks

3 visits (in-person)

Follow-up

Participants are monitored for safety and effectiveness after treatment

4 weeks

Treatment Details

Interventions

• MyoTrain

Trial Overview The study compares standard motor imagery training (Control Group A) to the MyoTrain system (Group B) in helping individuals control their prosthetic devices after trans-radial amputation. Participants will be randomly assigned to one of these two groups.

Participant Groups

Group I: Experimental Experimental Treatment 1 Intervention

Participants will be provided with the take-home MyoTrain system, which includes the MyoTrain armband, iPad, and MyoTrain software. Participants will progress through the training modules of the MyoTrain software, starting with eliciting paired single DoF antagonistic movements and ending with the proportional control of complex, 2-DoF hand and wrist movements.

Group II: Control Active Control 1 Intervention

Participants will be provided motor imagery exercises that involve brief attempts to move the missing limb in a similar manner to how they would control their pattern recognition system to strengthen their muscles. These exercises do not involve any real-time control feedback.

MyoTrain is already approved in United States for the following indications:

Approved in United States as MyoTrain for:

• Pre-prosthetic training for individuals with upper limb loss

Who Is Running the Clinical Trial?

Infinite Biomedical Technologies

Lead Sponsor

Trials

7

Recruited

160+

National Institute of Neurological Disorders and Stroke (NINDS)

Collaborator

Trials

1,403

Recruited

655,000+

Johns Hopkins University

Collaborator

Trials

2,366

Recruited

15,160,000+

Hanger Clinic: Prosthetics & Orthotics

Collaborator

Trials

11

Recruited

520+

Findings from Research

A virtual reality simulator effectively trained 13 military personnel with upper extremity loss to control advanced myoelectric prostheses, achieving over 95% accuracy in basic motion tasks and significant improvements in more complex tasks over time.

The training allowed participants to generate distinct muscle contraction patterns in their residual limbs, which were accurately interpreted by the prosthetic control system, highlighting the potential for intuitive control of prosthetic devices.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Virtual Integration Environment as an Advanced Prosthetic Limb Training Platform. Perry, BN., Armiger, RS., Yu, KE., et al.[2020]

In a study involving seven participants aged 9 to 62 with unilateral congenital upper limb amputation, all successfully controlled a myoelectric prosthesis with multiple degrees of freedom using pattern recognition technology, achieving proficiency comparable to their sound limb.

The results indicate that both children and adults can effectively use myoelectric prostheses with pattern recognition control, suggesting significant potential benefits for this population in enhancing their functional capabilities.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluating the Ability of Congenital Upper Extremity Amputees to Control a Multi-Degree of Freedom Myoelectric Prosthesis. Kaluf, B., Gart, MS., Loeffler, BJ., et al.[2022]

The Modular Prosthetic Limb (MPL) system allows individuals with upper extremity amputations to control an advanced prosthesis with greater accuracy and efficiency, enabling them to manage an average of eight motion classes compared to just three with conventional prostheses.

Participants showed significant improvements in their ability to control the MPL, as indicated by the Assessment of Capacity for Myoelectric Control (ACMC) scores, suggesting that the MPL can effectively enhance functionality for those with limb loss.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical evaluation of the revolutionizing prosthetics modular prosthetic limb system for upper extremity amputees. Yu, KE., Perry, BN., Moran, CW., et al.[2022]

Participants using augmented reality (AR) training with limb loading showed a significantly greater increase in their ability to complete tasks with a real prosthesis compared to those who trained without loading or performed simple muscle training.

The group that trained with limb loading not only improved more but also reached peak performance faster, indicating that incorporating limb loading into AR training can enhance the transfer of motor skills from virtual to physical environments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation. Hunt, CL., Sun, Y., Wang, S., et al.[2023]

A novel mobile, game-based training approach for myoelectric prostheses significantly improved muscle control, sequencing, and isolation in able-bodied participants, suggesting it could enhance training for amputees.

Participants found the game-based training highly usable and motivating, indicating its potential to increase rehabilitation success rates for amputees by allowing training outside clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Mobile, Game-Based Training for Myoelectric Prosthesis Control. Winslow, BD., Ruble, M., Huber, Z.[2020]

Current prostheses for individuals with upper limb amputation or congenital limb difference are inadequate, leading to issues like rejection and pain, highlighting the need for improved solutions.

Emerging technologies such as robotic limbs and osseointegrated prostheses show promise in meeting user needs, but they also introduce new risks that must be carefully evaluated through user perspectives and feedback.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Upper extremity prosthesis user perspectives on unmet needs and innovative technology. Benz, HL., Jia Yao, ., Rose, L., et al.[2022]

A standardized training protocol for using a body-powered bypass prosthesis was developed and tested with six volunteers over ten two-hour sessions, revealing that optimal training lengths were three sessions for the modified Southampton Hand Assessment and six sessions for the Box and Blocks Test.

The study found a weak correlation between prepositioning and performance scores, suggesting that prepositioning may not significantly enhance the effectiveness of training with the prosthesis as previously thought.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Creating a standardized, quantitative training protocol for upper limb bypass prostheses. Bloomer, C., Wang, S., Kontson, K.[2020]

A new low-cost, multi-user functional-test socket for transradial prosthetics was developed, allowing for rapid fitting and use in research, costing under $10 and taking less than 10 minutes to adjust for different users.

The socket did not hinder participants' performance in functional tasks or affect the quality of electromyography signals, and it was comfortable enough for at least 2 hours of use, promoting greater involvement of end-users in myoelectric prosthetic research.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Multi-User Transradial Functional-Test Socket for Validation of New Myoelectric Prosthetic Control Strategies. Hansen, TC., Citterman, AR., Stone, ES., et al.[2023]

A study involving 11 able-bodied participants showed that a video game-based rehabilitation protocol significantly improved muscle control metrics, such as fine accuracy and endurance, after just one session of EMG-controlled games.

The findings suggest that using engaging video games for training can enhance the controllability of myoelectric prostheses, potentially increasing motivation and effectiveness for users, especially if started before receiving the final prosthesis.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Game-Based Rehabilitation for Myoelectric Prosthesis Control. Prahm, C., Vujaklija, I., Kayali, F., et al.[2020]

A new training system for myoelectric prosthetic hands was developed to help upper limb amputees learn control schemes and muscle isolation, using a remote-controlled car for practice.

Preliminary testing with eight nonamputee volunteers showed that users improved their skills significantly during training, indicating the system's potential effectiveness for future use with amputees.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A novel myoelectric training device for upper limb prostheses. Clingman, R., Pidcoe, P.[2014]

The MSMS software tool allows researchers and engineers to simulate and evaluate the performance of neural prosthetic limbs before they are constructed, enhancing safety and efficiency in development.

MSMS also provides a virtual training environment for patients, enabling them to learn how to control their prostheses effectively before actual use, which can improve rehabilitation outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

MSMS software for VR simulations of neural prostheses and patient training and rehabilitation. Davoodi, R., Loeb, GE.[2011]

The myoelectric postural control algorithm was tested in a laboratory setting with two trans-radial amputees, showing that it can be integrated into existing prosthetic systems.

The postural controller achieved an average of 66% hand function compared to an intact limb, indicating its potential effectiveness, although results were mixed when compared to a commercial state-of-the-art system.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Myoelectric Postural Control Algorithm for Persons With Transradial Amputations: A Consideration of Clinical Readiness. Segil, JL., Kaliki, R., Uellendahl, J., et al.[2022]

References

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

Virtual Integration Environment as an Advanced Prosthetic Limb Training Platform. [2020]

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

Evaluating the Ability of Congenital Upper Extremity Amputees to Control a Multi-Degree of Freedom Myoelectric Prosthesis. [2022]

3. England pubmed.ncbi.nlm.nih.gov

Clinical evaluation of the revolutionizing prosthetics modular prosthetic limb system for upper extremity amputees. [2022]

4. England pubmed.ncbi.nlm.nih.gov

Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation. [2023]

5. Switzerland pubmed.ncbi.nlm.nih.gov

Mobile, Game-Based Training for Myoelectric Prosthesis Control. [2020]

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

Upper extremity prosthesis user perspectives on unmet needs and innovative technology. [2022]

7. England pubmed.ncbi.nlm.nih.gov

Creating a standardized, quantitative training protocol for upper limb bypass prostheses. [2020]

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

A Multi-User Transradial Functional-Test Socket for Validation of New Myoelectric Prosthetic Control Strategies. [2023]

9. Canada pubmed.ncbi.nlm.nih.gov

Game-Based Rehabilitation for Myoelectric Prosthesis Control. [2020]

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

A novel myoelectric training device for upper limb prostheses. [2014]

11. Netherlands pubmed.ncbi.nlm.nih.gov

MSMS software for VR simulations of neural prostheses and patient training and rehabilitation. [2011]

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

A Myoelectric Postural Control Algorithm for Persons With Transradial Amputations: A Consideration of Clinical Readiness. [2022]