Integrated Pico-Tesla Resolution Magnetoresistive Sensors for Miniaturised Magnetomyography

Abstract

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.

Magnetoresistive Sensors and Piezoresistive Accelerometers for Vibration Measurements: A Comparative Study

“…The stacks consist of 464 magnetic tunnel junction (MTJ) elements connected in a series to minimize the 1/ f noise of the sensor [15] [16]. As depicted in Figure 1, from data measured at INL premises, the sensor presents a short linear range (4 mT) that is adequate for applications that require high sensitivity levels, such as vibration in motors, metallic canister detection in high speed convey belts, among others.…”

High-Precision Biomagnetic Measurement System Based on Tunnel Magneto-Resistive Effect

“…The sensor sensitivity can be calculated from a slope of the experimental transfer curve and represent how much the sensor responds to field changes, while the noise level will determine the limit of detection. According to theoretical calculation and experiment outcomes, the best overall noise performance is obtained with large arrays of large area sensors [13]. Therefore, 1102 TMR sensors are connected as 38 rows and 29 columns in series to minimize sensor 1/f noise.…”

Developing a Data-Driven Unsupervised Pattern Recognition Approach for Sensor Signal Anomaly Detection

“…A spintronic sensor based on tunnel magnetoresistance (TMR) [36], [37] is placed nearby a machine which measures a changing magnetic field around that machine. This sensor was previously used in some other proof of concepts [38], [39], [40] such as real-time interaction system for eye movement gesture control [38] which successfully classified eye movements. In this work, the TMR sensor's output signal which somehow shows the machine's behaviour is then fed into an intelligent system in order to detect signal patterns and subsequently anomalies.…”