Robotic exoskeletons have gained recent acclaim within the field of rehabilitative medicine as a promising modality for functional restoration for those individuals with extremity weakness. However, their use remains largely confined to research institutions, frequently operating as a means of static extremity support as motor detection methods remain unreliable. Peripheral nerve interfaces have arisen as a potential solution to this shortcoming; however, due to their inherently small amplitudes, these signals can be difficult to differentiate from background noise, lowering their overall motor detection accuracy. As current interfaces rely on abiotic materials, inherent material breakdown can occur alongside foreign body tissue reaction over time, further impacting their accuracy. The Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was designed to overcome these noted complications. Consisting of a segment of free muscle graft secured circumferentially to an intact peripheral nerve, the construct regenerates and becomes reinnervated by the contained nerve over time. In rats, this construct has demonstrated the ability to amplify a peripheral nerve's motor efferent action potentials up to 100 times the normal value through the generation of compound muscle action potentials (CMAPs). This signal amplification facilitates high accuracy detection of motor intent, potentially enabling reliable utilization of exoskeleton devices.