COMPLETE CONTROL System Gen2
Overview
The Coapt COMPLETE CONTROL System Gen2 is an advanced control solution designed to provide intuitive and natural functionality for powered myoelectric prostheses for upper extremity amputees. Leveraging a novel combination of machine learning and artificial intelligence (AI), the system decodes the electrical signals from a user’s muscles, translating their natural intent into seamless prosthetic movements.
Reengineered from its first generation, the Gen2 system offers enhanced intuitive prosthesis control, overcoming the limitations of conventional methods that are often cumbersome and unnatural. It features an AI-enabled Control Coach, a layer of intelligence designed to assist users in optimizing control by providing automated feedback and instruction.
The system is an add-on controller kit that integrates seamlessly with virtually every major powered prosthetic arm and hand component on the market. It enables quick and easy calibration, often with a single button press or through its mobile application, allowing users to personalize and adapt their control on the go.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Machine learning and AI for intuitive control
- Pattern recognition technology for decoding muscle signals
- AI-enabled Control Coach for optimizing control
- Control Companion mobile app (iOS and Android)
- Quick and easy calibration (one-button or app-based)
- Compatibility with most major powered prosthetic arm components
- Eliminates the need for mode-switching
- Decodes natural intent muscle signal patterns
- Smaller size and more efficient operation (Gen2 improvement)
- Adaptive algorithms
Use Cases
- Intuitive control of upper-limb prostheses
- Enhancing functionality for individuals with limb loss or limb difference
- Restoring more natural movement for bionic prosthetics
- Optimizing control through automated feedback and instruction
- Personalizing prosthesis control
- Reducing reliance on conventional, cumbersome control methods
What Physicians Need to Know
For clinicians, the Coapt COMPLETE CONTROL System Gen2 offers advanced myoelectric pattern recognition for intuitive control of upper-limb prostheses. It is crucial to guide patients through the calibration process, which can be done quickly and on-the-go, or more comprehensively via the Control Companionu00ae mobile app. Emphasize the AI-enabled Control Coach for optimizing user control and providing feedback on calibration quality. The system's compatibility with a wide range of prosthetic components allows for flexible prescription and integration into existing setups.
The COMPLETE CONTROL System Gen2 is designed as an add-on controller kit that seamlessly integrates with nearly every major powered prosthetic arm component, offering plug-and-play ability. It is compatible with over 400 combinations and configurations of prosthetic hands, wrists, and elbows from various manufacturers. The system also connects wirelessly to the Control Companionu00ae mobile app (iOS and Android) for user interface and control adjustments.
Details
| Category | Neurology AI, Surgical AI |
| Pricing | Unknown |
| Deployment | Embedded system within the prosthesis |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated The COMPLETE CONTROL System Gen2 received Class II FDA Clearance (K191083) on May 24, 2019. It is cleared as an advanced control solution for powered myoelectric prostheses for upper extremity amputees, employing pattern recognition technology. |
| Integrations | |
| EHR | Not specified |
| Specialties | Orthopedics, Physical Medicine & Rehab, Plastic Surgery |
What the Web Says
The Coapt COMPLETE CONTROL System Gen2 is a myoelectric pattern-recognition system for controlling bionic upper limbs, utilizing machine learning and AI to adapt to users and provide intuitive control. It received Class II clearance from the U.S. Food and Drug Administration and was recognized with a Silver award in the Rehabilitation and Assistive-Technology Products category at the 2021 Medical Design Excellence Awards. The system aims to improve users' quality of life by offering more intuitive and adaptive control compared to previous prosthetic arm control systems that relied on switching and gross user movements.
Overall: PositiveStrengths
- Improved quality of life for users.
- More intuitive and natural movement due to AI-enabled Control Coach.
- Adaptive algorithms that learn and adjust to the user.
- Faster recalibration (one minute) for on-the-go adjustments.
- Advanced features and hardware platform compared to other products on the market.
- Significant improvements in control with increased EMG channels, including decreased classification error, completion time, and increased path efficiency.
Limitations
- Previous prosthetic arm control systems relied on switching and gross user movements that were not 100% intuitive.
- Conventional systems provided no adaptation to the user as their control needs changed.
- The system's accuracy is strongly dependent on the quality of the training sets used to generate ML models.
- Federal law restricts this device to sale by or on the order of a physician.
- Should not be used to operate a motor vehicle due to potential unintended movements.
- Should not be used in immediate proximity to active implanted devices without professional assurance of safety.
Based on reviews from: The Robot Report, Artificial Intelligence in Translational Medicine - MDPI, Implications of EMG channel count: enhancing pattern recognition online prosthetic testing, Co-Adaptation in Upper-Limb Prosthetics: Interactive Machine Learning applied to Myocontrol - mediaTUM, Should bionic limb control mimic the human body? Impact of control strategy on bionic hand skill learning - PMC, accessdata.fda.gov, Coapt Engineering, Medical Design Excellence Awards (MDEA) Unveils 2021 Winners - Business Wire, Biomimetic versus arbitrary motor control strategies for bionic hand skill learning
Last updated: 2026-07-21
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Coapt Control Companionu00ae Mobile App Tutorial
