Clinical trial NCT04272489: Pattern Recognition Prosthetic Control
Official title: Efficacy of Control System Adaptation in Improving Upper-Extremity Prosthetic Limb Wear Time in a Real-World Setting, a Randomized Crossover Trial
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Prosthesis User
Congenital Amputation of Upper Limb
Amputation; Traumatic, Limb
Keywords: pattern recognition
home trial
randomized cross-over trial
prosthesis
electromyography
Lead sponsor: Coapt, LLC
Sponsor class: INDUSTRY
Collaborators: name: Congressionally Directed Medical Research Programs
First posted: 2020-02-17
Enrollment: 9
Sex: ALL
Minimum age (years): 18
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: CROSSOVER
Intervention 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.
Primary purpose: TREATMENT

Brief 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 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.


Eligibility criteria: Inclusion Criteria:

* 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.

Exclusion Criteria:

* 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.

Primary outcomes:
measure: Differences in prosthetic wear time
timeFrame: We will record total prosthetic wear time during the course of each in-home 8-week period.
Secondary outcomes:
measure: Differences in calibration frequency
timeFrame: We will record calibration frequency during the course of each in-home 8-week period.
measure: Changes in virtual game performance
timeFrame: 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.
measure: RIC's Orthotics Prosthetics User Survey
timeFrame: 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.
measure: Prosthetic user survey
timeFrame: Participants will complete the survey at the end of their study participation (17 weeks).
measure: Differences in classification accuracy
timeFrame: 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.
Other outcomes:
Locations:
city: Chicago
country: United States
facility: Coapt, LLC
state: Illinois
Study officials:
affiliation: Coapt, LLC
name: Blair Lock, MScE
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: Scheme 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.
citation: Simon 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.
citation: Kyranou 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.