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 a tiny magnetic field are bulky, costly, and require working in a temperature-controlled environment. Developing miniaturized, low cost and room temperature magnetic sensors provide an avenue to enhance this research field. Herein, we present integrated tunneling magnetoresistive (TMR) array for room temperature MMG applications. TMR sensors we redeveloped with low-noise analog front-end circuitry to detect the MMG signals without and with averaging at a high signal-to-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 the finite-element method (FEM) considering the effect of distance from the observation point to the magnetic field source.
- Tunneling magnetoresistance ,
- Muscles ,
- Magnetic sensors ,
- Magnetic field measurement ,
- Magnetic fields ,
Detecting weak bio magnetic fields, Magnetomyography (MMG), first formally proposed in 1972 by Cohen and Gilver . With the development of efficient magnetic technologies, this non-invasive technique becomes more attractive because it has great potential to improve medical diagnosis and health monitoring, and to develop rehabilitation robotics where thehuman-machine interface can assist the disabled with limb difference to perform essential activities of daily living . The MMG signals are recorded as components of the magnetic field vector versus time, which is generated the action potentialfrom electric currents travelling along with skeletal musclefibres. Compared with a well-established Electromyography (EMG) method, the MMG measurement has become an effective alternative means due to its significantly higher spatial resolution despite the same temporal resolution as the EMG signals . Both signals are directly from the Maxwell-Ampère law, shown in Fig. 1. The magnitude of magnetic fieldreduces significantly with the distance between the origin andthe sensor, thereby with MMG spatial resolution is uplifted .In addition, the non-invasive MMG offer vector information of the muscle movement, long-term biocompatibility with issue, a higher signal-to-noise, and better positioning and fast screening of sensors without electric contacts , –.State-of-the-art EMG measurements are even using needle recording probes, which is possible to accurately assess muscle activity but painful and limited to tiny areas with poor spatial sampling points . Moreover, magnetic sensors with biocompatible materials can be fully packaged to form a miniaturized implantable system . However, detecting ultra-low MMG signals is not an easy task. Compared with the magnitude of the EMG signal in the scale of milli-volts, the MMG signal is extremely small and just in the range of pico (10−12) to femto (10−15) Tesla , decreasing with the distance between the measurement pointand the skeletal muscle. Currently, the most common approach is utilizing superconducting quantum interference devices (SQUIDs). They led the development of the MMG until now since it is the most sensitive device so far with the femto-Tesla detection ability, and possibly achieve atto-Tesla detection with averaging . Nevertheless, their high cost, bulky weight and operation at the low-temperature environment limit the spread of these techniques. As time goes by, optimally-pumped magnetometers (OPMs) from QuSpin Inc. have been performed in the MMG study , . The new generation of OPM offers small physical size with significantly improved limit-of-detection below 100 fT/√Hz. Unfortunately, it is still rather complex for the sensor setup with proper operation.Current experiments based on SQUIDs and OPMs for MMG sensing are conducted in heavily shielded rooms, which are expensive and bulky for a daily basis. As a consequence, a miniaturised, highly sensitive, low-cost and low-power MMG system must be fulfilled to perform at room temperature. We have previously demonstrated a high-performance Hall sensor in CMOS technology with its integrated readout circuit .However, the Hall sensors require a highly stable DC power supply to excite the Hall effect and a complex interface circuit to process collected weak Hall voltages under surrounding noise . However, spintronic sensors , especially our previous structure of the tunnel magnetoresistance (TMR) sensors , offer high sensitivity than giant magnetoresistive (GMR) sensors for weak magnetic field sensing. Recent spintronics-based MMG measurement was carried out by the GMR sensor . Its detection limit of 3.5 nT cannot meet the requirement of the surface measurement (pico -Tesla level).
In summary, we showed the first result of highly sensitive TMR-recorded ultra-low MMG signals from the human hand muscle at room temperature. As an effective alternative to SQUIDs, this new method demonstrates the viability of theminiaturized TMR sensor for medical and biological researchat a safe manner. By combining both electrical and magnetic sensors, we can distinguish different signals based on complementary information from the muscle activities , which is targeted, repeatable and safe. The test subject strained and relaxed the hand muscle in a magnetically shielded box and double stainless-steel chambers. The MMG recording wasachieved by using the EEG signal as a trigger. An amplitude of 200 pT was observed in a wide frequency band with the SNR over 20. In addition, the FEM simulations and 3D printed compact muscle model were investigated to validate the experimental results. The future multi-channel and real-time measurements with a flexible TMR sensor array and on-chip magnetic background noise cancellation may lead to further improvements in simplification and miniaturization of the MMG system and reduce the cost.
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FULL Paper PDF file:Integrated Pico-Te s l a R e s o l u t I o n Magnetoresistive Sensors for miniaturized Magnetomyography
S. Zuo et al.,
Integrated Pico-Tesla Resolution Magnetoresistive Sensors for Miniaturised Magnetomyography
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Montreal, QC, Canada, 2020, pp. 3415-3419,
PDF reference and original file: Click here
Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.