Advanced Prosthetic Control Algorithm for Limb Weakness

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Overseen ByJacob Wilson, BS
Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: University of Utah
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to improve how people with limb weakness control advanced orthotic devices (robotic braces) using muscle signals. Researchers are testing a new algorithm, the Experimental Control Algorithm, which could enhance the devices' responsiveness to muscle movements. Participants will use either a current control system or the new experimental one. This study suits individuals who had their first stroke at least six months ago and experience chronic weakness on one side of their body. As an unphased trial, it offers participants the chance to contribute to innovative research that could enhance future treatments for limb weakness.

Do I need to stop my current medications for this trial?

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

What prior data suggests that this advanced prosthetic control algorithm is safe for limb weakness?

Research has shown that high-density electromyography (HD-EMG) control systems have been well-received in past studies. These systems use muscle signals to operate devices like exoskeletons and have improved the control of prosthetic devices without causing major side effects.

In some studies, HD-EMG enhanced device performance by increasing responsiveness and reliability. Although no serious side effects were reported, some individuals might experience slight discomfort from the electrodes, which resemble sticky patches on the skin that read muscle signals. Overall, these treatments have shown promise in safely improving device control.12345

Why are researchers excited about this trial?

Researchers are excited about the High-Density EMG Control Algorithm because it offers a novel way to enhance prosthetic limb control for individuals with limb weakness. Unlike standard control systems like MyoPro, which rely on binary muscle signals, this new algorithm uses advanced predictive algorithms to map residual muscle activity to intended movements. This approach could significantly improve precision and responsiveness, offering users a more natural and intuitive prosthetic experience.

What evidence suggests that this trial's algorithms could be effective for limb weakness?

Research has shown that the High-Density EMG Control Algorithm, which participants in this trial may receive, can significantly enhance the control of prosthetic devices. High-density electromyography (HDEMG) records detailed muscle activity, aiding in accurate movement prediction. Studies indicate that this method allows for more precise control of electronic devices, such as robotic braces, by linking muscle activity to intended actions. As a result, individuals might experience better control and use of their limbs. Early findings suggest that this technology could improve the quality of life for those with weak limbs. Meanwhile, the Clinically Available Control Algorithm, serving as the control condition in this trial, uses a commercially available device, the MyoPro, for binary control of the orthosis.12367

Are You a Good Fit for This Trial?

This trial is for individuals who have had their first-ever stroke at least 6 months ago, resulting in paresis or hemiparesis. They must be able to move the arm opposite of the affected side but cannot currently be incarcerated.

Inclusion Criteria

My opposite arm moves normally.
I have had one stroke in my life.
I have long-term weakness on one side of my body.
See 1 more

Exclusion Criteria

You are currently in jail or prison.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants use the orthotic device with different control algorithms for up to 2 hours

2 hours
1 visit (in-person)

Follow-up

Participants are monitored for safety and effectiveness after using the device

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

  • Commercially Available Control Algorithm
  • Experimental Control Algorithm
Trial Overview The study tests a new control algorithm against a standard one used in advanced myoelectric orthotic devices that help people with limb paralysis by using muscle signals to control a robotic brace.
How Is the Trial Designed?
2Treatment groups
Experimental Treatment
Active Control
Group I: High-Density EMG Control AlgorithmExperimental Treatment1 Intervention
Group II: Clinically Available Control Algorithm (MyoPro)Active Control1 Intervention

Find a Clinic Near You

Who Is Running the Clinical Trial?

University of Utah

Lead Sponsor

Trials
1,169
Recruited
1,623,000+

Published Research Related to This Trial

Filtered control with filtered feedback showed better short-term performance in myoelectric prosthesis control, indicating it is effective for immediate task execution.
Raw control with raw feedback led to stronger internal model development, which is crucial for improving long-term performance, suggesting that richer feedback can enhance user understanding of the control system.
Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies.Shehata, AW., Scheme, EJ., Sensinger, JW.[2019]
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.
A novel myoelectric training device for upper limb prostheses.Clingman, R., Pidcoe, P.[2014]
Recent advances in pattern recognition control for myoelectric prostheses show promise for improving control in transhumeral amputees, even those who have not undergone reinnervation surgery.
A study with able-bodied control subjects demonstrated that a two degree-of-freedom pattern recognition system can be accurately trained using just four EMG channels, offering better real-time control compared to traditional amplitude control methods.
A comparison of direct and pattern recognition control for a two degree-of-freedom above elbow virtual prosthesis.Toledo, C., Simon, A., Muñoz, R., et al.[2020]

Citations

Advances in HD-EMG interfaces and spatial algorithms for ...Upper limb amputation significantly affects daily functioning and quality of life. Although myoelectric prostheses offer a promising avenue ...
High-density electromyography for effective gesture-based ...High-density electromyography (HDEMG) can detect myoelectric activity as control inputs to a variety of electronically-controlled devices.
Advanced Prosthetic Control Algorithm for Limb WeaknessThe purpose of this study is to improve control of myoelectrically-controlled advanced orthotic devices (an exoskeleton device that use the body's muscle ...
Improving Myoelectric Prosthetic and Orthotic Limb ControlThe purpose of this study is to improve control of myoelectrically-controlled advanced orthotic devices (an exoskeleton device that use the body's muscle ...
High-density surface EMG signal quality enhancement via ...This study proposed and systematically investigate the capability of optimized filtering techniques in denoising EMG signal towards improving its overall ...
Intuitive real-time control strategy for high-density ...This paper proposes a highly intuitive, responsive and reliable real-time myoelectric hand prosthesis control strategy
(PDF) High-density electromyography for effective gesture- ...High-density electromyography (HDEMG) can detect myoelectric activity as control inputs to a variety. of electronically-controlled devices.
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