Muscles are the actuators of all human actions, from daily work and life to communication and expression of emotions. Myography records the signals from muscle activities as an interface between machine hardware and human wetware, granting direct and natural control of our electronic peripherals. Regardless of the significant progression as of late, the conventional myographic sensors are still incapable of achieving the desired high-resolution and non-invasive recording. This paper presents a critical review of state-of-the-art wearable sensing technologies that measure deeper muscle activity with high spatial resolution, so-called super-resolution. This paper classifies these myographic sensors according to the different signal types (i.e., biomechanical, biochemical, and bioelectrical) they record during measuring muscle activity. By describing the characteristics and current developments with advantages and limitations of each myographic sensor, their capabilities are investigated as a super-resolution myography technique, including: (i) non-invasive and high-density designs of the sensing units and their vulnerability to interferences, (ii) limit-of-detection to register the activity of deep muscles. Finally, this paper concludes with new opportunities in this fast-growing super-resolution myography field and proposes promising future research directions. These advances will enable next-generation muscle-machine interfaces to meet the practical design needs in real-life for healthcare technologies, assistive/rehabilitation robotics, and human augmentation with extended reality.

The study and measurement of the magnetic field from the skeletal muscle is called Magnetomyography (MMG). These magnetic fields are produced by the same ion currents which give rise to the electrical signals that are recorded with electromyography (EMG). Layers between the muscle and skin surface, known as volume conduction, play a critical role during the measurement. This paper presents the volume conduction effect on the electrical and magnetic signals with the finitedifference time-domain simulations using Sim4Life. The effects of 1 mm fat on the recorded electrical and magnetic signals from the skin surface have been evaluated in both EMG and MMG. The results indicate that due to 1 mm fat, the electrical signals decrease over 60% through traveling across layers between the muscle and skin surface, while these layers are transparent to the magnetic field. In a similar simulation procedure, when the new fibers are recruited, the interference among electrical signals makes the strength of recorded signals behave non-linearly proportional to the increasing number of active muscle fibers. Sim4Life simulations show that the recorded magnetic signals do not have the same trajectory as electrical signals. Hence, the changes in EMG signals caused by the volume conduction effect can result in signal misinterpretations.

Neuromuscular diseases are a prevalent cause of prolonged and severe suffering for patients, and with the global population aging, it is increasingly becoming a pressing concern. To assess muscle activity in NMDs, clinicians and researchers typically use electromyography (EMG), which can be either non-invasive using surface EMG, or invasive through needle EMG. Surface EMG signals have a low spatial resolution, and while the needle EMG provides a higher resolution, it can be painful for the patients, with an additional risk of infection. The pain associated with the needle EMG can pose a risk for certain patient groups, such as children. For example, children with spinal muscular atrophy (type of NMD) require regular monitoring of treatment efficacy through needle EMG; however, due to the pain caused by the procedure, clinicians often rely on a clinical assessment rather than needle EMG. Magnetomyography (MMG), the magnetic counterpart of the EMG, measures muscle activity non-invasively using magnetic signals. With super-resolution capabilities, MMG has the potential to improve spatial resolution and, in the meantime, address the limitations of EMG. This article discusses the challenges in developing magnetic sensors for MMG, including sensor design and technology advancements that allow for more specific recordings, targeting of individual motor units, and reduction of magnetic noise. In addition, we cover the motor unit behavior and activation pattern, an overview of magnetic sensing technologies, and evaluations of wearable, non-invasive magnetic sensors for MMG.

Some magnetoelectric sensors require predefined external magnetic fields to satisfy optimal operation depending on their resonance frequency. While coils commonly generate this external magnetic field, a microelectromechanical systems (MEMS) resonator integrated with permanent magnets could be a possible replacement. In this proof-of-concept study, the interaction of a MEMS resonator and the ME sensor is investigated and compared with the standard approach to achieve the best possible sensor operation in terms of sensitivity. The achievable sensor sensitivity was evaluated experimentally by generating the magnetic excitation signal by a coil or a small-sized MEMS resonator. Moreover, the possibility of using both approaches simultaneously was also analysed. The MEMS resonator operated with 20Vppat 1.377 kHz has achieved a sensor sensitivity of 221.21mV/T. This sensitivity is comparable with the standard approach, where only a coil for sensor excitation is used. The enhanced sensitivity of 277.0mV/T could be identified by generating the excitation signal simultaneously by a coil and the MEMS resonator in parallel. In conclusion, these MEMS resonator methods can potentially increase the sensitivity of the ME sensor even further. The unequal excitation frequency of the MEMS resonator and the resonance frequency of the ME sensor currently limit the performance. Furthermore, the MEMS resonator as a coil replacement also enables the complete sensor system to be scaled down. Therefore, optimizations to match both frequencies even better are under investigation.

Arteriovenous grafts (AVGs) are indispensable lifesaving implants for chronic kidney disease (CKD) patients undergoing hemodialysis. However, AVGs will often fail due to postoperative complications such as cellular accumulation termed restenosis, blood clots, and infections, which are dominant causes of morbidity and mortality. A new generation of hemodialysis implants equipped with biosensors and multi-band antennas for wireless power and telemetry systems that can detect specific pathological parameters and report AVGs' patency would be transformative for CKD. Our study proposes a compact dualband implantable antenna for hemodialysis monitoring applications. It operates in 1.4 GHz and 2.45 GHz for wireless power transfer and biotelemetry purposes. The miniaturized antenna with a current size of 5 × 5 × 0.635 mm 3 exhibits wide bandwidth (300 MHz at 1.4 GHz band and 380 MHz at 2.45 GHz band), along with good impedance matching at two resonance frequencies. In addition, simulations are performed separately in a three-layer homogenous phantom and a realistic human body model. Measurements of the proposed antenna are evaluated in minced pork. The measured results of the fabricated antenna prototype are closely harmonized with the simulation ones, and the effect of different proportions of fat tissue in pork mince was analyzed, to verify the sensitivity of the antenna to the contacting medium. The specific absorption rate (SAR) and link budget calculation are also analyzed. Finally, the wireless biotelemetry function of the proposed antenna is realized and visualized by adopting a pair of nRF24L01 wireless transceivers, and sustainable and stable wireless data transmission characteristics are shown at a high data rate of 2 Mbps with up to 20 cm transmission distance.