Enhancing the versatility of wireless biopotential acquisition for myoelectric prosthetic control

Neuromuscular implants: Interfacing with skeletal muscle for improved clinical translation of prosthetic limbs

After an amputation, advanced prosthetic limbs can be used to interface with the nervous system and restore motor function. Despite numerous breakthroughs in the field, many of the recent research advancements have not been widely integrated into clinical practice. This review highlights recent innovations in neuromuscular implants-specifically those that interface with skeletal muscle-which could improve the clinical translation of prosthetic technologies. Skeletal muscle provides a physiologic gateway to harness and amplify signals from the nervous system. Recent surgical advancements in muscle reinnervation surgeries leverage the "bio-amplification" capabilities of muscle, enabling more intuitive control over a greater number of degrees of freedom in prosthetic limbs than previously achieved. We anticipate that state-of-the-art implantable neuromuscular interfaces that integrate well with skeletal muscle and novel surgical interventions will provide a long-term solution for controlling advanced prostheses. Flexible electrodes are expected to play a crucial role in reducing foreign body responses and improving the longevity of the interface. Additionally, innovations in device miniaturization and ongoing exploration of shape memory polymers could simplify surgical procedures for implanting such interfaces. Once implanted, wireless strategies for powering and transferring data from the interface can eliminate bulky external wires, reduce infection risk, and enhance day-to-day usability. By outlining the current limitations of neuromuscular interfaces along with potential future directions, this review aims to guide continued research efforts and future collaborations between engineers and specialists in the field of neuromuscular and musculoskeletal medicine.

Fully Implantable Low-Power High Frequency Range Optoelectronic Devices for Dual-Channel Modulation in the Brain

Wireless optoelectronic devices can deliver light to targeted regions in the brain and modulate discrete circuits in an animal that is awake. Here, we propose a miniaturized fully implantable low-power optoelectronic device that allows for advanced operational modes and the stimulation/inhibition of deep brain circuits in a freely-behaving animal. The combination of low power control logic circuits, including a reed switch and dual-coil wireless power transfer platform, provides powerful capabilities for the dissection of discrete brain circuits in wide spatial coverage for mouse activity. The actuating mechanism enabled by a reed switch results in a simplified, low-power wireless operation and systematic experimental studies that are required for a range of logical operating conditions. In this study, we suggest two different actuating mechanisms by (1) a magnet or (2) a radio-frequency signal that consumes only under 300 µA for switching or channel selection, which is a several ten-folds reduction in power consumption when compared with any other existing systems such as embedded microcontrollers, near field communication, and Bluetooth. With the efficient dual-coil transmission antenna, the proposed platform leads to more advantageous power budgets that offer improved volumetric and angular coverage in a cage while minimizing the secondary effects associated with a corresponding increase in transmitted power.

Decoding of muscle activity from the sensorimotor cortex in freely behaving monkeys

Remarkable advances have recently been made in the development of Brain-Machine Interface (BMI) technologies for restoring or enhancing motor function. However, the application of these technologies may be limited to patients in static conditions, as these developments have been largely based on studies of animals (e.g., non-human primates) in constrained movement conditions. The ultimate goal of BMI technology is to enable individuals to move their bodies naturally or control external devices without physical constraints. Here, we demonstrate accurate decoding of muscle activity from electrocorticogram (ECoG) signals in unrestrained, freely behaving monkeys. We recorded ECoG signals from the sensorimotor cortex as well as electromyogram signals from multiple muscles in the upper arm while monkeys performed two types of movements with no physical restraints, as follows: forced forelimb movement (lever-pull task) and natural whole-body movement (free movement within the cage). As in previous reports using restrained monkeys, we confirmed that muscle activity during forced forelimb movement was accurately predicted from simultaneously recorded ECoG data. More importantly, we demonstrated that accurate prediction of muscle activity from ECoG data was possible in monkeys performing natural whole-body movement. We found that high-gamma activity in the primary motor cortex primarily contributed to the prediction of muscle activity during natural whole-body movement as well as forced forelimb movement. In contrast, the contribution of high-gamma activity in the premotor and primary somatosensory cortices was significantly larger during natural whole-body movement. Thus, activity in a larger area of the sensorimotor cortex was needed to predict muscle activity during natural whole-body movement. Furthermore, decoding models obtained from forced forelimb movement could not be generalized to natural whole-body movement, which suggests that decoders should be built individually and according to different behavior types. These results contribute to the future application of BMI systems in unrestrained individuals.

The myokinetic control interface: tracking implanted magnets as a means for prosthetic control

Upper limb amputation deprives individuals of their innate ability to manipulate objects. Such disability can be restored with a robotic prosthesis linked to the brain by a human-machine interface (HMI) capable of decoding voluntary intentions, and sending motor commands to the prosthesis. Clinical or research HMIs rely on the interpretation of electrophysiological signals recorded from the muscles. However, the quest for an HMI that allows for arbitrary and physiologically appropriate control of dexterous prostheses, is far from being completed. Here we propose a new HMI that aims to track the muscles contractions with implanted permanent magnets, by means of magnetic field sensors. We called this a myokinetic control interface. We present the concept, the features and a demonstration of a prototype which exploits six 3-axis sensors to localize four magnets implanted in a forearm mockup, for the control of a dexterous hand prosthesis. The system proved highly linear (R² = 0.99) and precise (1% repeatability), yet exhibiting short computation delay (45 ms) and limited cross talk errors (10% the mean stroke of the magnets). Our results open up promising possibilities for amputees, demonstrating the viability of the myokinetic approach in implementing direct and simultaneous control over multiple digits of an artificial hand.