Advances in upper limb loss rehabilitation: the role of targeted muscle reinnervation and regenerative peripheral nerve interfaces

Book excerpt: Upper limb loss results in significant physical and psychological impairment and is a major financial burden for both patients and healthcare services. Current myoelectric prostheses rely on electromyographic (EMG) signals captured using surface electrodes placed directly over antagonistic muscles in the residual stump to drive a single degree of freedom in the prosthetic limb (e.g., hand open and close). In the absence of the appropriate muscle groups, patients rely on activation of biceps/triceps muscles alone (together with a mode switch) to control all degrees of freedom of the prosthesis. This is a non-physiological method of control since it is non-intuitive and contributes poorly to daily function. This leads to the high rate of prosthetic abandonment. Targeted muscle reinnervation (TMR) reroutes the ends of nerves in the amputation stump to nerves innervating “spare” muscles in the amputation stump or chest wall. These then become proxies for the missing muscles in the amputated limb. TMR has revolutionised prosthetic control, especially for high-level amputees (e.g., after shoulder disarticulation), resulting in more intuitive, fluid control of the prosthesis. TMR can also reduce the intensity of symptoms such as neuroma and phantom limb pain. Regenerative peripheral nerve interface (RPNI) is another technique for increasing the number of control signals without the limitations of finding suitable target muscles imposed by TMR. This involves wrapping a block of muscle around the free nerve ending, providing the regenerating axons with a target organ for reinnervation. These RPNIs act as signal amplifiers of the previously severed nerves and their EMG signals can be used to control prosthetic limbs. RPNI can also reduce neuroma and phantom limb pain. In this review article, we discuss the surgical technique of TMR and RPNI and present outcomes from our experience with TMR.