Targeted Muscle Reinnervation for Prosthetic Control

Targeted muscle reinnervation (TMR) is a surgical procedure, whereby nerves without muscle targets after extremity amputation are transferred to residual stump muscles. Thereby, the control of prosthesis is improved by increasing the number of independent muscle signals. The authors describe indications for TMR to improve prosthetic control and present standard nerve transfer matrices suitable for transhumeral and glenohumeral amputees. In addition, the perioperative procedure is described, including preoperative testing, surgical approach, and postoperative rehabilitation. Based on recent neurophysiological insights and technological advances, they present an outlook into the future of prosthetic control combining TMR and implantable electromyographic technology.

Broadband Prosthetic Interfaces: Combining Nerve Transfers and Implantable Multichannel EMG Technology to Decode Spinal Motor Neuron Activity

Modern robotic hands/upper limbs may replace multiple degrees of freedom of extremity function. However, their intuitive use requires a high number of control signals, which current man-machine interfaces do not provide. Here, we discuss a broadband control interface that combines targeted muscle reinnervation, implantable multichannel electromyographic sensors, and advanced decoding to address the increasing capabilities of modern robotic limbs. With targeted muscle reinnervation, nerves that have lost their targets due to an amputation are surgically transferred to residual stump muscles to increase the number of intuitive prosthetic control signals. This surgery re-establishes a nerve-muscle connection that is used for sensing nerve activity with myoelectric interfaces. Moreover, the nerve transfer determines neurophysiological effects, such as muscular hyper-reinnervation and cortical reafferentation that can be exploited by the myoelectric interface. Modern implantable multichannel EMG sensors provide signals from which it is possible to disentangle the behavior of single motor neurons. Recent studies have shown that the neural drive to muscles can be decoded from these signals and thereby the user's intention can be reliably estimated. By combining these concepts in chronic implants and embedded electronics, we believe that it is in principle possible to establish a broadband man-machine interface, with specific applications in prosthesis control. This perspective illustrates this concept, based on combining advanced surgical techniques with recording hardware and processing algorithms. Here we describe the scientific evidence for this concept, current state of investigations, challenges, and alternative approaches to improve current prosthetic interfaces.