Coapt pattern recognition restores daily living for two amputees

AI system

System: Coapt pattern recognition myoelectric control (Coapt, Chicago, IL) on a multiarticulating hand and wrist
Model: Not assessed
Release: Not assessed
Application developer: Coapt LLC
Role: Not assessed
Configuration: Not assessed
Inputs and outputs: Not assessed
Autonomy: Not assessed
Workflow: Stable implanted attachment delivering consistent electrode contact. Pattern-recognition classifier trained on the patient's own EMG patterns. Structured training with the software after surgery.
Human oversight: Not assessed
Relation to AI: The Coapt software is a machine-learning pattern-recognition controller that maps electromyographic patterns to hand and wrist motions. The report attributes improved control to training with this software on an osseointegrated attachment. So the AI contribution is entangled with the surgical attachment and cannot be isolated.
AI contribution: The Coapt software is a machine-learning pattern-recognition controller that maps electromyographic patterns to hand and wrist motions. The report attributes improved control to training with this software on an osseointegrated attachment. So the AI contribution is entangled with the surgical attachment and cannot be isolated.

Outcome identifiers: Not assessed
Benefit: Two transulnar amputees given Coapt pattern-recognition prostheses on osseointegration implants regained activities of daily living.
Category: Improved Accessibility
Status: Not assessed
Beneficiary groups: People. Society.
Beneficiaries: Not assessed
Reach: Not assessed
Distribution and access: Not assessed
Duration: Not assessed
Expected?: Yes
Costs and harms: Not assessed

Studies: Not assessed
Study design: Not assessed
Measurement: Not assessed
Setting and sample: Not assessed
Measures: Not assessed
Comparison: direct myoelectric control
Results: Result: significant improvements in the Assessment of Capacity for Myoelectric Control (ACMC) outcome measure while using pattern recognition control compared to direct control.
Additional value from AI: Not assessed
Limitations: Not assessed
Denominators: Not assessed
Materials for replication: Not assessed

Participants: Developer: Coapt LLC. Operator: Hospital for Special Surgery, New York (Department of Limb Lengthening and Complex Reconstruction; the affiliation is given for the first author).
Jurisdictions: Benefit: New York, New York, United States. Developer: United States. Operator: United States.
Ownership and control: Not assessed
Dependencies: Not assessed
Cross-border connections: Not assessed
Geopolitical implications: Not assessed

Conditions for replication: Sufficient residual muscle signals to separate grip and wrist classes. Osseointegration without loosening over the follow-up period. Clinician-supervised calibration and training.
Replication attempts: 1 follow-up entries. Benefit recurred: 1.
Later findings: 31 January 2023. A later randomized home-use study of transradial amputees confirmed broader grip use and better myoelectric control with Coapt pattern recognition than with direct control.
Availability: Not assessed
Institutional decision: Not assessed
Grounds: Not assessed
Action and result: Not assessed
Success criterion: Not assessed

Assessed benefits: People. Society.
Depth: People: 2. Society: 1.
Reasons: People: Two identifiable patients gained prosthetic control enough for daily living activities, documented at 18-month and 2-year follow-up. The abstract has no validated functional scores, so life-changing is unsupported. Society: A two-patient case report demonstrating feasibility of combining osseointegration with pattern-recognition control; no population-level effect shown.
Observed or intended: Not assessed
Rubric: Not assessed
Assessor and date: Not assessed
Alternative assessments: Not assessed
Fill: The deployer's account

Kind: Not assessed
Related entries: Not assessed
Field: Rehabilitation medicine / upper-limb prosthetics. Amputee prosthetic care.
Purpose: Pattern-recognition control of a multiarticulating myoelectric hand and wrist for people with upper-limb amputation
Dates: Date basis unassessed: 2021 (precision unassessed). Updated: 21 October 2026.
Stage: Not assessed
Version: SHA-256: a39530618e07…

Peer-reviewed study Developer

Simon AM, Turner KL, Miller LA, Potter BK, Beachler MD, Dumanian GA, Hargrove LJ, Kuiken TA (2023). User Performance With a Transradial Multi-Articulating Hand Prosthesis During Pattern Recognition and Direct Control Home Use. IEEE Trans Neural Syst Rehabil Eng.
Case report Deployer

Jaime KM, Reif TJ, Kafedzic H, Garrison G, Dhawan J, Rozbruch SR (2021). Attachment of a Myoelectric Prosthesis After Transulnar Osseointegration Implantation: A 2-Patient Case Study. JBJS Case Connector 11(4).