Magnetism‐based systems are widely utilized for sensing and imaging biological phenomena, for example, the activity of the brain and the heart. Magnetomyography (MMG) is the study of muscle function through the inquiry of the magnetic signal that a muscle generates when contracted. Within the last few decades, extensive effort has been invested to identify, characterize and quantify the magnetomyogram signals. However, it is still far from a miniaturized, sensitive, inexpensive and low‐power MMG sensor. Herein, the state‐of‐the‐art magnetic sensing technologies that have the potential to realize a low‐profile implantable MMG sensor are described. The technical challenges associated with the detection of the MMG signals, including the magnetic field of the Earth and movement artifacts are also discussed. Then, the development of efficient magnetic technologies, which enable sensing pico‐Tesla signals, is advocated to revitalize the MMG technique. To conclude, spintronic‐based magnetoresistive sensing can be an appropriate technology for miniaturized wearable and implantable MMG systems.

Magnetomyography (MMG) with superconducting quantum interference devices (SQUIDs) enabled the measurement of very weak magnetic fields (femto to pico Tesla) generated from the human skeletal muscles during contraction. However, SQUIDs are bulky, costly, and require working in a temperature-controlled environment, limiting wide-spread clinical use. We introduce a lowprofile magnetoelectric (ME) sensor with analog frontend circuitry that has sensitivity to measure pico-Tesla MMG signals at room temperature. It comprises magnetostrictive and piezoelectric materials, FeCoSiB/AlN. Accurate device modelling and simulation are presented to predict device fabrication process comprehensively using the finite element method (FEM) in COMSOL Multiphysics. The fabricated ME chip with its readout circuit was characterized under a dynamic geomagnetic field cancellation technique. The ME sensor experiment validate a very linear response with high sensitivities of up to 378 V/T driven at a resonance frequency of f res = 7.76 kHz. Measurements show the sensor limit of detections of down to 175 pT/ÝHz at resonance, which is in the range of MMG signals. Such a small-scale sensor has the potential to monitor chronic movement disorders and improve the end-user acceptance of human-machine interfaces.

Spintronic sensors, that are based on the tunnellingmagnetoresistive (TMR) effect, have been utilized in detecting low magnetic fields. However, still no computer-based model of these devices is available to integrated circuit designer to implement them in a hybrid spintronic-CMOS system. We developed a finite element method (FEM)-based model of a MgO-barrier TMR device in COMSOL Multiphysics ®. The parameters of this model were extracted from the state-of-the-art fabrication and experimental data. Results were compared with respect to the model geometry and the used material. The proposed TMR sensor model offers a linear response with a high TMR ratio of 233% at 10 mV power supply. The model was exported to Cadence © Spectre to create a compact model using Verilog-A language. The developed sensor model was simulated with its analog front-end in same environment. This model provided a reliable benchmark for modelling of the future hybrid spintronic-CMOS developments.

Magnetomyography utilizes magnetic sensors to record small magnetic fields produced by the electrical activity of muscles, which also gives rise to the electromyogram (EMG) signal typically recorded with surface electrodes. Detection and recording of these small fields requires sensitive magnetic sensors possibly equipped with a CMOS readout system. This paper presents a highly sensitive Hall sensor fabricated in a standard 0.18 µm CMOS technology for future low-field MMG applications. Our experimental results show the proposed Hall sensor achieves a high current mode sensitivity of approximately 2400 V/A/mT. Further refinement is required to enable measurement of MMG signals from muscles.

Magnetomyography (MMG) is the measurement of magnetic signals generated in the skeletal muscle of humans by electrical activities. However, current technologies developed to detect such tiny magnetic field are bulky, costly and require working at the temperature-controlled environment. Developing a miniaturized, low cost and room temperature magnetic sensors provide an avenue to enhance this research field. Herein, we present an integrated tunnelling magnetoresistive (TMR) array for room temperature MMG applications. TMR sensors were developed with low-noise analogue front-end circuitry to detect the MMG signals without and with averaging at a high signalto-noise ratio. The MMG was achieved by averaging signals using the Electromyography (EMG) signal as a trigger. Amplitudes of 200 pT and 30 pT, corresponding to periods when the hand is tense and relaxed, were observed, which is consistent with muscle simulations based on finite-element method (FEM) considering the effect of distance from the observation point to the magnetic field source.