Prosthesis UserAdaptationNCT04272489
Pattern Recognition Prosthetic Control
A study of Prosthesis User and Congenital Amputation of Upper Limb, run by Coapt, LLC at 1 site in United States.
Trial summary
Many different factors can degrade the performance of an upper limb prosthesis users control with electromyographic (EMG)-based pattern recognition control. Conventional control systems require frequent recalibration in order to achieve consistent performance which can lead to prosthetic users choosing to wear their… Read more about this study
- Who is it for?
- Ages 18 to 70 years
- Conditions the study is for
- Prosthesis User, Congenital Amputation of Upper Limb, Amputation; Traumatic, Limb
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 9 participants
- Where
- 1 siteUnited States
- Study dates
- 17 Dec 2020to 20 May 2022
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 70 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Subjects have an upper-limb difference (congenital or acquired) at the transradial (between the wrist and elbow), elbow disarticulation (at the elbow), transhumeral (between the elbow and shoulder), or shoulder disarticulation (at the shoulder) level.
- Subjects are suitable to be, or already are, a Coapt pattern recognition user (Coapt Complete Control Gen 2).
- Subjects are between the ages of 18 and 70.
Who cannot join
- Subjects with significant cognitive deficits or visual impairment that would preclude them from giving informed consent or following instructions during the experiments, or the ability to obtain relevant user feedback discussion.
- Subjects who are non-English speaking.
- Subjects who are pregnant.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Efficacy of Control System Adaptation in Improving Upper-Extremity Prosthetic Limb Wear Time in a Real-World Setting, a Randomized Crossover Trial
Many different factors can degrade the performance of an upper limb prosthesis users control with electromyographic (EMG)-based pattern recognition control. Conventional control systems require frequent recalibration in order to achieve consistent performance which can lead to prosthetic users choosing to wear their device less. This study investigates a new adaptive pattern recognition control algorithm that retrains, rather than overwrite, the existing control system each instance users recalibrate. The study hypothesis is that such adaptive control system will lead to more satisfactory prosthesis control thus reducing the need for recalibration and increasing how often users wear their device. Participants will wear their prosthesis as they would normally at-home using each control system (adaptive and non-adaptive) for an 8-week period with an intermittent 1-week washout period (17 weeks total). Prosthetic usage will be monitored during each period in order to compare user wear time and recalibration frequency when using adaptive or non-adaptive control. Participants will also play a set of virtual games on a computer at the start (0-months), mid-point (1-months) and end (2-months) of each period that will test their ability to control prosthesis movement using each control system. Changes in user performance will be evaluated during each period and compared between the two control systems. This study will not only evaluate the effectiveness of adaptive pattern recognition control, but it will be done at-home under typical and realistic prosthetic use conditions.
- Being tested
- EMG-Pattern Recognition Controller
- Keywords
- pattern recognition, home trial, randomized cross-over trial, prosthesis, electromyography
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
EMG-Pattern Recognition ControllerDevice
Also called Coapt Complete Control Gen2
Using an electromyographic (EMG)-based pattern recognition controller to move an upper limb prosthetic device in a home trial.
| Study group | Role | What they receive |
|---|---|---|
| Adaptive Control | Experimental | The adaptive control system updates the pattern recognition control algorithm by incorporating new EMG data each instance the prosthetic user recalibrates their device. Receives: Device: EMG-Pattern Recognition Controller |
| Non-Adaptive Control | Active comparator | The conventional, non-adaptive control systems resets the pattern recognition control algorithm by deleting old EMG data each instance the prosthetic user recalibrate their device. Receives: Device: EMG-Pattern Recognition Controller |
What is being measured
The primary outcome is the main question the study is designed to answer.
Differences in prosthetic wear time
We will record each instance participants turn on or off their pattern recognition device throughout the home trial. Prosthetic wear time is defined as the cumulative amount of time participants keep their pattern recognition device turned on during the course of each in-home 8-week period. We will perform a statistical analysis to compare wear time when using each type of pattern recognition control system (adaptive and non-adaptive). We will complete repeated measures analysis of variance with subject as a random factor, order of control system used as a fixed variable, and wear time as a fixed variable.
Measured: We will record total prosthetic wear time during the course of each in-home 8-week period.
Secondary outcomes (5)
Differences in calibration frequency
We will record each instance participants recalibrate their pattern recognition device throughout the home trial. We will perform a statistical analysis to compare the frequency of calibrations when using each control system (adaptive and non-adaptive). We will complete a repeated measures analysis of variance with subject as a random factor, order of control system used as a fixed variable, and wear time as a fixed variable.
Measured: We will record calibration frequency during the course of each in-home 8-week period.
Changes in virtual game performance
Participants will complete two virtual games called Simon Says and In-the-Zone using the Coapt Complete ControlRoom desktop application. Both games will test how well participants control motion of virtual objects using their pattern recognition device. We will measure their overall control performance by computing completion rate, movement time, path efficiency. We will perform a statistical analysis to compare virtual game performance when using each control system. We will complete a repeated measures analysis of variance with subject as a random factor, order of pattern recognition control system used as a fixed variable, and each performance metric as a fixed variable.
Measured: Participants will complete the virtual games at the start (0-months), mid-point (1-months) and end (2-months) of each in-home 8-week period.
RIC's Orthotics Prosthetics User Survey
Participants will complete the Upper Extremity Functional Status module from RIC's Orthotics Prosthetics User Survey (OPUS). The OPUS asks prosthetic users to rate the level of difficulty (from very easy to very difficult) in performing upper arm/hand functions using their pattern recognition device. Survey data will be evaluated using rating scale analysis (Rasch model).
Measured: Participants will complete the OPUS at the start (0-months) and end (2-months) of each 8-week period. of each in-home 8-week period.
Prosthetic user survey
Participants will complete a survey or phone interview to provide feedback on which control system they prefer between adaptive or non-adaptive. Participants will inform whether they prefer the control system they used in the first or second 8-week period.
Measured: Participants will complete the survey at the end of their study participation (17 weeks).
Differences in classification accuracy
Participants will be instructed to use their pattern recognition device to make a set of independent prosthesis motions and hold each motion for 3 seconds. For each motion, we will record the output motion class determined by their pattern recognition classifier every 50 ms. We will measure the performance of their classier when using each control system (adaptive and non-adaptive) by computing the classification accuracy which is defined as the number of correct classifications over the total number of classifications for each motion. We will perform a statistical analysis to compare classification accuracy when using each control system. We will complete a repeated measures analysis of variance with subject as a random factor, order of pattern recognition control system used as a fixed variable, and classification accuracy as a fixed variable.
Measured: We will record classification accuracy at the start (0-months), mid-point (1-months) and end (2-months) of each in-home 8-week period.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Feb 2020
- Study start17 Dec 2020
- Primary completion20 May 2022
- Study completion20 May 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (4)Papers the sponsor has linked to this study.
- Other trials for Prosthesis UserStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Crossover
- Model description
- The study is a randomized crossover home trial consisting of two 8-week periods with an intermittent 1-week washout period (17 weeks total). Participants will use either adaptive control or non-adaptive control during the first 8-week period then switch to using the opposite control style during the second 8-week period.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 9 participants (actual)
Sponsor and investigators
- Lead sponsor
- Coapt, LLC
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Congressionally Directed Medical Research Programs
- Responsible party
- Sponsor
- Investigators
- Blair Lock, MScE, Principal investigator, Coapt, LLC
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04272489
- Sponsor's protocol ID
- 120190044
- Other IDs
- W81XWH-17-1-0645
- Acronym
- Adaptation
- Status last verified
- Oct 2022
- First submitted
- 13 Feb 2020
- Last updated
- 20 Oct 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- Yes: Only de-identified individual participant data collected during the study may be shared. This includes any experimental data that will underlie results in a publication such as EMG data, prosthesis usage data, virtual game data and surveys and questionnaires.
Publications
Chicoine CL, Simon AM, Hargrove LJ. Prosthesis-guided training of pattern recognition-controlled myoelectric prosthesis. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:1876-9. doi: 10.1109/EMBC.2012.6346318.
PubMed 23366279Scheme E, Englehart K. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. J Rehabil Res Dev. 2011;48(6):643-59. doi: 10.1682/jrrd.2010.09.0177.
PubMed 21938652Simon AM, Hargrove LJ, Lock BA, Kuiken TA. Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses. J Rehabil Res Dev. 2011;48(6):619-27. doi: 10.1682/jrrd.2010.08.0149.
PubMed 21938650Kyranou I, Vijayakumar S, Erden MS. Causes of Performance Degradation in Non-invasive Electromyographic Pattern Recognition in Upper Limb Prostheses. Front Neurorobot. 2018 Sep 21;12:58. doi: 10.3389/fnbot.2018.00058. eCollection 2018.
PubMed 30297994
Study at a glance
From the registry record, last updated by the sponsor on 20 Oct 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Efficacy of Control System Adaptation in Improving Upper-Extremity Prosthetic Limb Wear Time in a Real-World Setting, a Randomized Crossover Trial
- ClinicalTrials.gov ID
- NCT04272489
- Acronym / sponsor ID
- Adaptation / 120190044
- Keywords
- pattern recognition, home trial, randomized cross-over trial, prosthesis, electromyography
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 9 participants (actual)
- Lead sponsor
- Coapt, LLCIndustry (pharma, biotech, devices)
- Collaborators
- Congressionally Directed Medical Research Programs
- Study start
- 17 Dec 2020 (actual)
- Primary completion
- 20 May 2022 (actual)
- Study completion
- 20 May 2022 (actual)
- First posted
- 17 Feb 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Many different factors can degrade the performance of an upper limb prosthesis users control with electromyographic (EMG)-based pattern recognition control. Conventional control systems require frequent recalibration in order to achieve consistent performance which can lead to prosthetic users choosing to wear their device less. This study investigates a new adaptive pattern recognition control algorithm that retrains, rather than overwrite, the existing control system each instance users recalibrate. The study hypothesis is that such adaptive control system will lead to more satisfactory prosthesis control thus reducing the need for recalibration and increasing how often users wear their device. Participants will wear their prosthesis as they would normally at-home using each control system (adaptive and non-adaptive) for an 8-week period with an intermittent 1-week washout period (17 weeks total). Prosthetic usage will be monitored during each period in order to compare user wear time and recalibration frequency when using adaptive or non-adaptive control. Participants will also play a set of virtual games on a computer at the start (0-months), mid-point (1-months) and end (2-months) of each period that will test their ability to control prosthesis movement using each control system. Changes in user performance will be evaluated during each period and compared between the two control systems. This study will not only evaluate the effectiveness of adaptive pattern recognition control, but it will be done at-home under typical and realistic prosthetic use conditions.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- The study is a randomized crossover home trial consisting of two 8-week periods with an intermittent 1-week washout period (17 weeks total). Participants will use either adaptive control or non-adaptive control during the first 8-week period then switch to using the opposite control style during the second 8-week period.
| Arm | Type | Receives |
|---|---|---|
| Adaptive Control | Experimental | Device: EMG-Pattern Recognition ControllerThe adaptive control system updates the pattern recognition control algorithm by incorporating new EMG data each instance the prosthetic user recalibrates their device. |
| Non-Adaptive Control | Active comparator | Device: EMG-Pattern Recognition ControllerThe conventional, non-adaptive control systems resets the pattern recognition control algorithm by deleting old EMG data each instance the prosthetic user recalibrate their device. |
Who may qualify
- Ages
- 18 to 70 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Subjects have an upper-limb difference (congenital or acquired) at the transradial (between the wrist and elbow), elbow disarticulation (at the elbow), transhumeral (between the elbow and shoulder), or shoulder disarticulation (at the shoulder) level.
- Subjects are suitable to be, or already are, a Coapt pattern recognition user (Coapt Complete Control Gen 2).
- Subjects are between the ages of 18 and 70.
Key exclusion criteria (3 listed)
- Subjects with significant cognitive deficits or visual impairment that would preclude them from giving informed consent or following instructions during the experiments, or the ability to obtain relevant user feedback discussion.
- Subjects who are non-English speaking.
- Subjects who are pregnant.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| EMG-Pattern Recognition ControllerAlso: Coapt Complete Control Gen2Using an electromyographic (EMG)-based pattern recognition controller to move an upper limb prosthetic device in a home trial. | Device | Adaptive Control, Non-Adaptive Control |
Primary outcome
Differences in prosthetic wear time
Time frame: We will record total prosthetic wear time during the course of each in-home 8-week period.
We will record each instance participants turn on or off their pattern recognition device throughout the home trial. Prosthetic wear time is defined as the cumulative amount of time participants keep their pattern recognition device turned on during the course of each in-home 8-week period. We will perform a statistical analysis to compare wear time when using each type of pattern recognition control system (adaptive and non-adaptive). We will complete repeated measures analysis of variance with subject as a random factor, order of control system used as a fixed variable, and wear time as a fixed variable.
5 secondary outcomes
Differences in calibration frequency
Time frame: We will record calibration frequency during the course of each in-home 8-week period.
Changes in virtual game performance
Time frame: Participants will complete the virtual games at the start (0-months), mid-point (1-months) and end (2-months) of each in-home 8-week period.
RIC's Orthotics Prosthetics User Survey
Time frame: Participants will complete the OPUS at the start (0-months) and end (2-months) of each 8-week period. of each in-home 8-week period.
Prosthetic user survey
Time frame: Participants will complete the survey at the end of their study participation (17 weeks).
Differences in classification accuracy
Time frame: We will record classification accuracy at the start (0-months), mid-point (1-months) and end (2-months) of each in-home 8-week period.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Oct 2022.
- Background: PubMed 23366279Chicoine CL, Simon AM, Hargrove LJ. Prosthesis-guided training of pattern recognition-controlled myoelectric prosthesis. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:1876-9. doi: 10.1109/EMBC.2012.6346318.
- Background: PubMed 21938652Scheme E, Englehart K. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. J Rehabil Res Dev. 2011;48(6):643-59. doi: 10.1682/jrrd.2010.09.0177.
- Background: PubMed 21938650Simon AM, Hargrove LJ, Lock BA, Kuiken TA. Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses. J Rehabil Res Dev. 2011;48(6):619-27. doi: 10.1682/jrrd.2010.08.0149.
- Background: PubMed 30297994Kyranou I, Vijayakumar S, Erden MS. Causes of Performance Degradation in Non-invasive Electromyographic Pattern Recognition in Upper Limb Prostheses. Front Neurorobot. 2018 Sep 21;12:58. doi: 10.3389/fnbot.2018.00058. eCollection 2018.
- Individual participant dataSharing planned: Yes. Only de-identified individual participant data collected during the study may be shared. This includes any experimental data that will underlie results in a publication such as EMG data, prosthesis usage data, virtual game data and surveys and questionnaires.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Blair Lock, MScE principal investigator
Coapt, LLC
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study of Prosthesis User and Congenital Amputation of Upper Limb, run by Coapt, LLC at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 20 Oct 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Differences in prosthetic wear time (time frame: We will record total prosthetic wear time during the course of each in-home 8-week period.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04272489, which also lists 4 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Oct 2022; AzTrials last refreshed its copy on 27 Oct 2026.