Biomagnetic measurement system for detecting biomagnetic signals

Abstract

A biomagnetic sensor incorporating an integrated active noise cancellation unit that uses a gradiometer to remove ambient magnetic noise from a detection signal obtained from a tunneling magnetoresistance (TMR) sensor unit that indicates the magnetic field adjacent to biological tissue. Thus, ambient magnetic noise can be removed in real time at the front end of the sensor (e.g., as part of the circuitry in the sensor body itself). The active noise cancellation technology proposed herein can be effective enough to enable the use of biomagnetic sensors in unshielded environments (i.e., environments affected by the Earth's magnetic field, for example), thereby significantly expanding the potential applications of the sensor.

Description

[Technical Field]

[0001] FIELD OF THE INVENTION The present invention relates to a system for measuring biomagnetic fields, and particularly, but not exclusively, to a wearable device for sensing biomagnetic signals. The system may incorporate a magnetic field sensor chip that utilizes a tunneling magnetoresistive (TMR) array in conjunction with active on-chip noise cancellation. [Background technology]

[0002] background It is known that muscle activity can be recorded using electrical sensors via superficial (on the skin) or deep (intramuscular) electromyography (EMG). A key challenge with EMG is the low spatial resolution of the sensors, which makes it difficult to selectively record from single motor units within the muscle. While intramuscular EMG, in which needle electrodes are pressed into the muscle tissue, can increase spatial resolution, this is painful and impairs muscle function. Furthermore, with long-term implants, such as those used for motor rehabilitation, the interface between the sensor's metal contacts and the human tissue changes over time, leading to infection and possible rejection by the body.

[0003] Rapid advances in micro- and nano-technologies have led to the noninvasive assessment of biomagnetism as an alternative paradigm to EMG. Biomagnetic signals have the same temporal resolution as their bioelectric counterparts but can offer significantly higher spatial resolution. Sensing magnetic fields also does not require electrical contacts during recording, and therefore, sensors can be fully encapsulated within biocompatible materials, minimizing the risk of infection [6].

[0004] However, providing practical devices capable of detecting biomagnetic signals remains a technical challenge, primarily due to the fact that biomagnetic signals have very small amplitudes. Although high temporal resolution can be achieved, achievable spatial resolution is constrained by limited sensor numbers, motion artifacts, inherently low signal-to-noise ratios (SNRs), and relatively high static and dynamic background magnetic noise [9].

[0005] Initial attempts to develop sensors for detecting small biomagnetic fields considered the use of superconducting quantum interference devices (SQUIDs)

[10] and optically-pumped magnetometers (OPMs).[5] Both approaches were limited by the need for large magnetically shielded chambers. These methods were bulky, expensive, consumed large amounts of power, and required a temperature-controlled environment.

[0006] More recently, spintronic sensors based on the magnetoresistive (MR) effect have revolutionized approaches to biomagnetic sensing due to their full compatibility with conventional silicon technology. These sensors can be integrated with readout circuits on standard CMOS processes in sub-mm diameter substrates to ultimately achieve on-chip signal conditioning, including amplification, filtering, noise, and drift cancellation

[11] . This phenomenon has led to the development of ultrasensitive MR sensors, which have the potential to detect magnetic fields in the picotesla range, suitable for biomagnetic signal levels, gradually replacing traditional thin-film magnetotransport devices such as Hall sensors

[12] .

[0007] Additionally, a miniaturized MR sensor area can improve the resolution of magnetic fields with small distance changes. Sensors placed closer to the neural source provide stronger signals. This makes MR sensors suitable for array applications with lower power requirements. Recently, giant magnetoresistive (GMR) sensors have been used to record weak biomagnetic signals. However, because the sensitivity of GMR sensors is in the nanotesla range, averaging has been necessary to improve the signal-to-noise ratio (SNR). Over the past decade, sensing at picotesla / √Hz levels has become possible using tunneling magnetoresistive (TMR) sensors, which can be highly miniaturized and operate at room temperature using sensor arrays.

[0008] A variety of potential applications for biomagnetic sensors have been identified, ranging from clinical diagnostics to human-computer interaction [1]. However, detection of weak biomagnetic fields originating from human active organs and tissues, including, for example, magnetocardiography (MCG) [2], [3], magnetoencephalography (MEG) [4], [5], magnetomyography (MMG) [6], [7], and magnetoneurography (MNG) [8], requires effective methods that offer both high spatial and temporal resolution. Summary of the Invention [Means for solving the problem]

[0009] Summary of the Invention Most generally, the present invention provides a biomagnetic sensor incorporating an integrated active noise cancellation unit that uses a gradiometer to remove ambient magnetic noise from a detection signal obtained from a tunneling magnetoresistance (TMR) sensor unit that is indicative of magnetic fields adjacent to biological tissue. Thus, ambient magnetic noise can be removed in real time at the front end of the sensor (e.g., as part of the circuitry in the sensor body itself). The active noise cancellation technology proposed herein can be effective enough to allow the biomagnetic sensor to be used in unshielded environments (i.e., environments affected by the Earth's magnetic field, for example), thereby significantly expanding the sensor's potential applications.

[0010] In a first aspect, the present invention may provide a biomagnetic sensor module comprising: a tunneling magnetoresistance (TMR) sensor unit configured to output a detection signal indicative of a magnetic field adjacent to biological tissue; a gradiometer unit configured to output a background signal indicative of ambient magnetic noise; a shielding element positioned between the TMR sensor unit and the gradiometer unit; an active noise cancellation unit configured to remove the background signal from the detection signal to generate a biomagnetic signal; an analog readout circuit configured to receive the biomagnetic signal and perform signal conditioning to generate an analog output; and an analog-to-digital converter (ADC) configured to generate a digital output signal from the analog output.

[0011] As used herein, the term "biomagnetic" refers to magnetic fields generated by electrical activity in biological tissue, e.g., nervous or muscular tissue. Typically, such magnetic fields are very weak, and a biomagnetic sensor is understood to be a device capable of detecting such weak magnetic fields, e.g., by having a sensitivity in the picotesla range, e.g., 50 pT / √Hz or less, preferably 20 pT / √Hz or less.

[0012] The TMR sensor unit may comprise a plurality of TMR sensors, each having an array of magnetic tunnel junctions fabricated on a substrate, the array being e.g., 12 mm 2 They can be fabricated using known nanoscale techniques to have a small footprint of less than 1000 nm.

[0013] The plurality of TMR sensors in the TMR sensor unit may comprise four TMR sensors in a Wheatstone bridge arrangement.

[0014] The gradiometer unit may comprise a three-axis gradiometer. An advantage of this arrangement is that the background signal may provide a consistent indication of ambient magnetic noise regardless of the orientation of the sensor module.

[0015] The gradiometer unit may use the same sensing modality as the TMR sensor unit. That is, the gradiometer unit may include multiple TMR sensors configured to detect ambient magnetic noise. The multiple TMR sensors may be configured similarly to the TMR sensors in the TMR sensor unit. For example, the gradiometer unit may include four TMR sensors in a Wheatstone bridge arrangement. Providing the same sensor configuration in both the gradiometer unit and the TMR sensor unit may allow the background signal to be directly comparable to the detected signal.

[0016] The biomagnetic sensor module may include a plurality of TMR sensor units, each TMR sensor unit positioned to detect a magnetic field adjacent to biological tissue and output a biomagnetic signal on a respective channel, and the biomagnetic sensor module further includes a multiplexer configured to selectively couple each respective channel to an analog readout circuit.

[0017] The biomagnetic sensor module may include a controller (eg, a microprocessor unit, etc.) configured to control the operation of the module.

[0018] The active noise cancellation unit may include a comparator (e.g., a differential amplifier or equivalent) configured to receive the background signal and the detection signal as inputs, whereby the background signal is subtracted from the detection signal to generate the biomagnetic signal. Thus, the active noise cancellation unit may operate directly on the outputs from the TMR sensor unit and the gradiometer unit, facilitating real-time cancellation before further signal processing occurs.

[0019] The biomagnetic sensor module may be configured to bring the TMR sensor unit into close proximity to a measurement location on a human or animal body. For example, the biomagnetic sensor module may include a skin-contacting interface made of a biocompatible material. The skin-contacting interface may form an outer surface, e.g., a base, of the biomagnetic sensor module. The TMR sensor unit may be disposed on the skin-contacting interface so that it is located as close as possible to the outer surface. The skin-contacting interface may include a thermal insulating layer disposed between the TMR sensor unit and the outer surface. The thermal insulating layer may inhibit heat conduction to maintain a stable temperature for the internal components of the biomagnetic sensor module (particularly the TMR sensor unit and the gradiometer unit).

[0020] The gradiometer unit may be located farther from the skin-contact interface than the TMR sensor unit. This configuration can prevent background signals from the gradiometer unit from being affected by magnetic fields generated in biological tissue. In one example, the gradiometer unit may be located more than 5 mm, preferably more than 10 mm, from the outer surface than the TMR sensor unit.

[0021] A shielding element installed between the TMR sensor unit and the gradiometer unit serves to further reduce the effect of magnetic fields generated within biological tissue on the background signal. The shielding element may be a magnetically permeable material such as a nickel-molybdenum alloy. The shielding element may be provided, for example, in the form of a foil or other sheet-like material as a layer to separate the TMR sensor unit and the gradiometer unit. The shielding element may allow the physical separation between the TMR sensor unit and the gradiometer unit to be minimized, for example, to 10 mm or less, without affecting the accuracy or sensitivity of the measurement.

[0022] The biomagnetic sensor module may further include a compensation unit configured to minimize baseline mismatch between the TMR sensor unit and the gradiometer unit, which may be caused by a combination of inherent mismatch between the sensors of the TMR sensor unit and the gradiometer unit and the effects of a shielding element. Here, reference to "baseline" refers to measurements obtained when the target signal is not present, i.e., when the TMR sensor unit is not disposed on the skin. The compensation unit may include a feedback circuit configured to receive a baseline output from the TMR sensor and the gradiometer unit and adjust the gradiometer unit to minimize the baseline output. In one example, the compensation unit may include an adjustable current source configured to generate a bias signal for the gradiometer unit, the bias signal being adjustable to minimize the baseline output. In another example, the compensation unit may include a variable gain amplifier connected between the gradiometer unit and the active noise cancellation unit, the gain of the variable gain amplifier being adjustable to minimize the baseline output.

[0023] In one example, the biomagnetic sensor module may have a layered structure including multiple functional layers stacked on top of each other, for example, with a skin-contacting interface layer at its base. The TMR sensor unit may be disposed on a primary sensing layer, and the gradiometer unit may be disposed on a secondary sensing layer parallel to and spaced apart from the primary sensing layer. In this regard, the above-mentioned shielding element may be provided as a layer between the primary and secondary sensing layers. The active noise cancellation unit and analog readout circuit may be disposed on one or more layers parallel to and spaced apart from the secondary sensing layer. Additional components, such as a controller, an ADC, and a power management unit, may be disposed on one or more additional layers. All layers may be surrounded or held together by a housing or shell.

[0024] The analog readout circuitry may be configured to cancel input offset and low frequency flicker noise, for example the analog readout circuitry may comprise a band pass filter and a common mode feedback circuit.

[0025] The biomagnetic sensor module may further include a wireless communication unit configured to transmit the digital output signal to a remote device. The remote device may be a smartphone, tablet, laptop, or desktop device. The wireless communication unit may be configured to transmit data using any suitable wireless protocol (e.g., Bluetooth, etc.). The wireless communication unit may also be capable of receiving information from the remote device, for example, to control the operation of the module or to update its firmware.

[0026] In another aspect, the present invention may provide a wearable biomagnetic sensing device comprising the biomagnetic sensor module described above. The wearable biomagnetic sensing device may be operable in an unshielded environment. The wearable biomagnetic sensing device may form part of a measurement system that also includes a remote computing device in communication with the biomagnetic sensor module, for example to receive a digital output signal.

[0027] In one example, a wearable biomagnetic sensing device may comprise a plurality of the biomagnetic sensor modules described above secured to a holding element attachable to a human body, which may be an elastic strap so that the device can be held around a user's arm or leg.

[0028] The present invention includes combinations of the described embodiments and preferred features except where such combinations are expressly impermissible or explicitly avoided.

[0029] Drawing Overview BRIEF DESCRIPTION OF THE DRAWINGS Embodiments and experiments illustrating the principles of the present invention will now be described with reference to the accompanying drawings. [Brief explanation of the drawings]

[0030] [Figure 1] 1 is a schematic diagram showing a layered structure of a biomagnetic sensor module according to an embodiment of the present invention. [Figure 2] FIG. 2 is a schematic diagram illustrating the components of a sensor array that can be used in the biomagnetic sensor module of FIG. 1. [Figure 3] 1 is a perspective view of a wearable biomagnetic detection device according to an embodiment of the present invention. [Figure 4] FIG. 2 is a schematic diagram illustrating the process flow between the functional components of the biomagnetic sensor module of FIG. 1. [Figure 5] FIG. 2 is a schematic diagram showing the configuration of a gradiometer in the biomagnetic sensor module of FIG. 1. [Figure 6] 10 is a graph illustrating the effect of a gradiometer compensation technique. [Figure 7]FIG. 2 is a schematic diagram illustrating a baseline compensation technique that can be used with the biomagnetic sensor module of FIG. 1. [Figure 8] FIG. 2 is a schematic diagram illustrating a readout circuit architecture that can be used in the biomagnetic sensor module of FIG. 1. [Figure 9A] 10 is a simulated graph showing the relative magnitude of MMG and noise magnetic signals processed by the biomagnetic sensor module. [Figure 9B] 10 is a simulated graph showing the relative magnitude of MMG and noise magnetic signals processed by the biomagnetic sensor module. [Figure 10] FIG. 1 is a cross-sectional view through a representation of muscle tissue used in a system for simulating biomagnetic potentials. [Figure 11A] FIG. 10 is a cross-sectional view through a representation of muscle tissue showing simulated electric field potentials in the muscle tissue in the absence of a fat layer. [Figure 11B] FIG. 11C is a cross-sectional view through the representation of the muscle tissue of FIG. 11B showing simulated magnetic field potentials. [Figure 11C] FIG. 10 is a cross-sectional view through a representation of muscle tissue showing simulated electric field potentials in muscle tissue with a fat layer around muscle fiber bundles. [Figure 11D] FIG. 11D is a cross-sectional view through the representation of muscle and adipose tissue of FIG. 11C showing simulated magnetic field potentials. [Figure 12] 11B is a graph showing the simulated electric field potential variation through lines AA and CC in FIGS. 11A and 11C. [Figure 13] 11B and 11D are graphs showing the simulated magnetic field potential variations through lines BB and DD in FIG. [Figure 14] 1 is a graph showing a simulated illustration of the variation of biomagnetic potential in muscle tissue with distance from its source. DETAILED DESCRIPTION OF THE INVENTION

[0031] Detailed Description of the Invention Aspects and embodiments of the present invention will now be described with reference to the accompanying drawings. Further aspects and embodiments will be apparent to those skilled in the art. All documents mentioned herein are incorporated by reference.

[0032] The present invention relates to biomagnetic measurement systems, and in particular to wearable biomagnetic sensing devices and biomagnetic sensing modules for use in such systems. The purpose of a biomagnetic measurement system is to detect or estimate biomagnetic potentials associated with muscle activity noninvasively at room temperature. Such a system may enable a greater understanding of what happens to muscles in areas that control limb movement.

[0033] As described in more detail below, the biomagnetic sensing module provides on-chip and real-time noise cancellation capabilities that reduce or cancel noise from the environment (e.g., the Earth's magnetic field, heat, and 1 / f noise) by combining multiple device and circuit technologies. These technologies enable the biomagnetic sensing module discussed herein to achieve, for the first time, noninvasive recording of magnetic biomedical signals from neurons, nerves, and muscles at room temperature without external shielding.

[0034] Generally speaking, the biomagnetic sensing devices discussed herein include one or more biomagnetic sensing modules each including a plurality of sensors, each having a plurality of tunneling magnetoresistance (TMR) elements arranged in an array, fabricated on a silicon substrate using, for example, conventional CMOS microfabrication techniques. Each sensing module may further include an integrated signal processing package, which includes an analog readout circuit configured to generate an analog output sent to an analog-to-digital converter (ADC). The ADC is connected to a microcontroller including a wireless communication module configured to communicate the digital output signal to a remote device for analysis. The sensors within each module may be configured to output signals on each of a plurality of channels. The analog readout circuit may be configured as multiple module units (one for each channel) connectable to the ADC by a multiplexer. As described below, the integrated signal processing package provides a noise cancellation function that can ensure that the detected biomagnetic potential is properly represented in the output signal.

[0035] 1 is a schematic diagram showing the stack-up structure of a biomagnetic sensor module 100 according to one embodiment of the present invention. The biomagnetic sensor module 100 is configured for use with a wearable biomagnetic sensing device intended to be worn against a user's skin in the area where measurements are to be taken.

[0036] The biomagnetic sensor module 100 in this example is constructed in a layered structure, with each layer intended to be parallel to the skin surface when worn. The layered structure includes a skin interface 102, which may comprise a biocompatible material or coating on the underside of the sensor module 100. As used herein, the terms "top" and "bottom" in reference to the biomagnetic sensor module 100 may be understood to refer to the intended orientation of the module relative to the skin surface during use. That is, the bottom of the module is intended to be closer to the skin surface than the top of the module during use. The skin interface 102 may facilitate easy attachment and removal of the device in various positions without the need to apply or remove gels and adhesives. Additionally, the use of biocompatible materials can ensure a comfortable fit. Examples of suitable biocompatible materials include nanocellulose, biocompatible polymers, or e-skin.

[0037] The skin interface 102 may further comprise an insulating layer, made from, for example, polyurethane, positioned to insulate the components of the sensor module 100 from heat generated by the user's body when the device is worn. This can ensure that the sensor array within the device operates at a consistent temperature, thereby avoiding the introduction of errors caused by thermal fluctuations.

[0038] Adjacent to the skin interface 102 is a magnetic sensing substructure 103 comprising three layers: a primary sensing layer 104, a shielding layer 106, and a secondary sensing layer 108. Each of the primary sensing layer 104 and the secondary sensing layer 108 comprises a plurality of tunneling magnetoresistance (TMR) sensors, as described below. The shielding layer 106 operates to magnetically isolate the primary sensing layer 104 from the secondary sensing layer 108. The shielding layer 106 is preferably formed of a magnetically permeable material such as a nickel-molybdenum alloy. In one example, the shielding layer 106 may be formed of MuMetal®, which has a composition of 80% nickel, 4.5% molybdenum, and the remainder iron to provide high magnetic susceptibility. As described in more detail below, the secondary sensing layer 108 is configured as a gradiometer to measure background magnetic field potentials that can be subtracted from signals detected by the primary sensing layer 104 as part of the noise cancellation functionality provided by the sensor module 100. The shielding layer 106 operates to shield the biomagnetic field from the secondary sensing layer 108. The strength of the biomagnetic field naturally decreases with distance from the skin surface according to the inverse square law. Because the secondary sensing layer 108 is already farther from the skin interface 102 than the primary sensing layer 104, it receives a weaker biomagnetic signal during use. However, the shielding layer 106 can enhance that isolation and ensure that a portion of the biomagnetic signal is not accidentally canceled out when the background magnetic field potential measured by the gradiometer is subtracted from the signal detected by the primary sensing layer 104.

[0039] 2 is a schematic diagram illustrating the components of a sensor unit 204 that can be used in the primary sensing layer 104 and the secondary sensing layer 108. In this example, the sensor unit 204 is configured with four sensors 206 in a Wheatstone bridge configuration, providing a signal on a first channel. The primary sensing layer 104 and the secondary sensing layer 108 of the sensor module 100 can be configured with multiple channels (e.g., eight or more), with the output of each channel coming from a separate sensor unit 204 attached to the associated layer. Thus, each of the primary sensing layer 104 and the secondary sensing layer 108 may comprise an assembly of sensor units 204.

[0040] Each of the sensors 206 in the sensor unit 204 comprises an array 208 of TMR sensor elements 210. Each TMR sensor element 210 in the array is a magnetic tunnel junction comprising two layers of ferromagnetic material 212, 216 separated by a very thin insulating layer 214. The top layer 212 is defined as the free layer because its magnetization direction can be freely changed, and the bottom layer 216 is referred to as the pinned layer because of its fixed magnetization direction when the sensor is fabricated. The sensor is configured to allow tunneling, which allows electrons to pass through the insulating layer 214 under certain conditions, causing the structure to exhibit spin-related magnetoresistance properties at room temperature.

[0041] The response of a TMR sensor corresponds to the change in resistance across the device with a changing magnetic field. For biomagnetic measurements, it is desirable for the response to be linear and free of hysteresis. Typically, optimal noise performance is achieved with large arrays of large-area sensors. In the example described herein, 1102 TMR sensor elements 210 are connected in series as 38 rows and 29 columns to minimize sensor 1 / f noise. Each TMR sensor element 210 was formed from a stack of the following layers (nm): 5Ta / 25CuN / 5Ta / 5Ru / 20IrMn / 2CoFe 30 / 0.85Ru / 2.6CoFe 40 B 20 / 1MgO[9kΩ·μm2] / 2CoFe 40 B 20 / 0.21Ta / 4NiFe / 0.20Ru / 6IrMn / 2Ru / 5Ta / 10Ru. The size of each TMR element is 100×100 μm. The size of the array 208 is 6×4 mm, which reduces the footprint of the sensor unit 204 to 20 mm 2 This means that it can be controlled as follows: Each array 210 on the sensor unit 204 is electrically connected to a respective electrode pad 218, and through that to the rest of the electronics.

[0042] The Wheatstone bridge structure is used to minimize temperature drift and to null the output signal when no magnetic field is applied. In the example described herein, four sensors 206 of the type described above are arranged in a full Wheatstone bridge configuration. With a bias current of 20 mA, the measured linear range of the sensors is approximately -1 Oe to 1 Oe. In the full bridge configuration, the measured resistance variation of each TMR sensor is 280 Ω·μm 2 / Oe. Therefore, 100 × 100 μm 2 For 1102 elements with an area of ​​, the sensitivity is calculated to be about 0.617 V / Oe.

[0043] Returning to FIG. 1 , module 100 further comprises signal processing circuitry 109 disposed above magnetic sensing substructure 103. Signal processing circuitry 109 is configured to perform on-device processing of signals received from the sensor unit. Signal processing circuitry 109 comprises an active noise cancellation unit 111, analog readout circuitry 110, and associated control circuitry 112, which may be disposed on their own layer or combined in one or more layers. The functionality of these layers is described in more detail below with reference to FIGS. 5-7.

[0044] The module 100 further comprises a wireless communication unit 114 that can be configured to communicate with a remote computer to transmit or receive data from the module. For example, the module 100 may be configured to transmit a post-processed output signal from the sensor unit to an external device for further analysis.

[0045] The module 100 further comprises a power management unit 116, which may include a battery (eg, a Li-ion cell) and associated control circuitry.

[0046] FIG. 3 shows an example of a wearable biomagnetic sensing device 300 incorporating multiple biomagnetic sensor modules 100 described above. Each module 100 is enclosed in a respective protective shell having a biocompatible underside through which the sensor unit 204 can detect biomagnetic signals. In this example, eight modules 100 are connected in a ring shape by an elastic strap 302. This configuration may be suitable for wearing on a user's wrist. The elastic strap 302 allows the device 300 to be easily worn, for example, by sliding it up and down the wrist, while also ensuring that the device remains in place during use, thereby ensuring that data can be collected with minimal movement artifacts. In another example, the device 300 may be used with a motion sensor that allows measured biomagnetic data to be combined with motion information.

[0047] FIG. 4 is a schematic diagram illustrating the process flow between the functional components of the biomagnetic sensor module 100 described above, as well as the communication between the module 100 and an external computing system 150. In this example, the control circuit 112 of the module 100 includes a microprocessor unit that interacts with the magnetic sensing substructure 103 and analog readout circuitry via respective voltage regulators 120, 122 under the control of power and amplitude calculation modules 136, 138 to ensure they receive a stable power supply. As described above, the magnetic sensing substructure 103 includes a primary sensing layer that provides signals from one or more sensor units, each having four TMR sensors in a Wheatstone bridge configuration. The control circuitry enables real-time readout of the signals from the sensor units. While the Wheatstone bridge preferably operates in voltage mode, it may also be possible to configure the module to be selectively operable in either voltage mode or current mode, for example, by using a selector actuator such as a toggle switch. The sensitivity of current mode to a given resistance change is twice as great as that of voltage mode. It is also highly desirable that the sensor output exhibit stability over a temperature range commensurate with the expected conditions of use (e.g., -20°C to 50°C). Integrating the TMR sensors into a full Wheatstone bridge provides a null voltage output in the absence of an external stimulus field, ensuring that each device in the arrangement outputs a complete signal that can be utilized by the differential amplifier.

[0048] As mentioned above, the magnetic sensing substructure 103 includes a gradiometer that measures dynamic magnetic background noise that can be subtracted from the signal measured by the primary sensing layer. Traditionally, magnetic sensing systems have had to operate in a magnetically shielded environment to reduce noise sources such as acoustic noise and magnetic and electric field disturbances from the Earth and surrounding equipment. In the present invention, the use of a gradiometer to compensate for dynamic magnetic background noise provides a device with sensitivity comparable to previous designs (approximately 20 pT) but with a higher dynamic range (targeting approximately 50 μT) without magnetic shielding.

[0049] FIG. 5 is a schematic diagram illustrating the configuration of a gradiometer in the active noise cancellation unit 111. The secondary sensing layer 106 includes multiple TMR sensor units of the same type as those in the primary sensing layer. However, instead of being configured to detect magnetic fields at the skin surface, the TMR sensor units in the secondary sensing layer 106 are configured as one or more gradiometers for recording dynamic magnetic background noise. In a preferred embodiment, three gradiometers are provided in a triaxial arrangement, with multiple TMR sensors integrated into a miniaturized Wheatstone bridge configuration for each axis of the gradiometer. The signals from these gradiometers are combined at the pickup sensor to provide a background signal that is independent of the device's orientation. The background signal is provided to the inverting input of a comparator 160 (a differential amplifier) ​​where it is subtracted from the signal provided by the primary sensing layer 104. The output of the comparator 160 is sent to the analog readout circuit 110. Thus, real-time compensation of dynamic magnetic background noise is performed at the front end of the module 100. This dramatically improves the system's immunity to large DC Earth magnetic fields and AC environmental noise.

[0050] Figure 6 shows a graph illustrating experimental results using a three-axis gradiometer in the manner outlined above. The proposed active noise cancellation is based on the principle of phase cancellation, where background magnetic noise 164 is recorded and inverted to create an "anti-noise," which is then added to the primary sensing layer output signal 162 containing the desired biomagnetic signal. The anti-noise signal cancels out the actual background magnetic noise to provide a compensation signal 166 that is output to the analog readout circuitry.

[0051] It is desirable to sample the ambient magnetic noise and align its phase as precisely as possible with the measurement signal to provide maximum attenuation. While 100% noise cancellation is not achievable in practical systems, the gradiometer compensation techniques disclosed herein can achieve 20-40 dB of noise reduction, thereby cutting the background noise level to 1 / 4-1 / 16 of its original level.

[0052] Returning to Figure 4, the output from the magnetic sensing substructure 103 is received by an analog readout circuit 110, which in this example includes a transimpedance amplifier (not shown), an instrumentation amplifier 124, a bandpass filter 126, a programmable gain amplifier 128, and an analog multiplexer 130. The analog multiplexer selectively connects signals from each channel in the magnetic sensing substructure 103 to an analog-to-digital converter (ADC) 132, which may be part of a microprocessor unit. The transimpedance amplifier is utilized to sense the current signal generated from the TMR sensor and convert it to a voltage readout with a maximum signal-to-noise ratio for subsequent signal processing. The bandpass filter 126 may be a high-order filter employing a Sallen-Key topology with a cutoff frequency of 300-500 Hz. In another example, the bandpass filter 126 may comprise a 20th-order Butterworth filter with a bandpass range of 30-300 Hz. The filtered signal is converted to digital data via ADC132, which in this example is an 18-bit successive approximation register ADC that offers high speed, high accuracy, low power and low cost.

[0053] The converted digital signal can be transmitted to an external computing system 150 via the wireless communication module 114. In this example, the external computing system 150 may include a computer (e.g., a laptop or desktop device) 152 and a smartphone 154, allowing the data to be displayed quickly and conveniently. Data may be communicated between the module 100 and the smartphone 154 via a conventional wireless communication protocol, such as Bluetooth®, through the module's protective shell 140. The protective shell 140 may be configured as a magnetic shield to reduce external magnetic noise within the module 100. The smartphone 154 may be connectable to communicate with the computer 152, for example, via a USB interface or a wireless connection, so that the digital signal can be extracted, classified, and displayed on a LabVIEW interface 156 on the computer.

[0054] 7 is a schematic diagram illustrating a baseline compensation arrangement that can be used in the biomagnetic sensor module described above. The baseline compensation arrangement is used to compensate for the inherent mismatch between the TMR sensor units in the primary sensing layer 104 and the secondary sensing layer 108, as well as the mismatch introduced by the shielding layer 106. This compensation can be achieved by controlling the bias of the reference TMR sensor unit (i.e., the gradiometer unit) in the secondary sensing layer 108 via an adjustable current source, or by using a variable gain low noise amplifier to modify the output signal from the secondary sensing layer 108 before it is received by a noise cancellation unit (e.g., a subtraction circuit such as the comparator 160 described above).

[0055] The baseline compensation arrangement is initialized by performing a preliminary step of measuring the baseline output voltages from the primary sensing layer 104 and the secondary sensing layer 108 in the absence of a target magnetic field (i.e., with the biomagnetic sensor module positioned away from the measurement location). This baseline output is due to the inherent mismatch between the TMR sensor units in the primary sensing layer 104 and the secondary sensing layer 108 and the mismatch introduced by the shielding layer 106. This mismatch can then be eliminated by adjusting the settings of the secondary sensing layer 108. In examples where an adjustable current source is used to provide a bias signal to the secondary sensing layer 108, this can be done by changing the bias signal received by the TMR sensor units in the secondary sensing layer 108. In this scenario, the secondary sensing layer 108 typically receives a different bias signal from the primary sensing layer 104. Alternatively, in examples where a variable gain amplifier is used at the output of the secondary sensing layer 108, this can be done by changing the gain of that amplifier. By using the output voltage from the readout circuit, a feedback loop is established to set the bias signal or gain level that minimizes the baseline output voltage difference. Once the optimal bias level or gain is found, it can be applied to the TMR sensor unit of the secondary sensing layer 108 or low-noise amplifier when the target magnetic field is measured, thereby reducing mismatches caused by the sensor and magnetic shielding and improving the overall sensitivity and accuracy of the gradiometer configuration.

[0056] 8 shows a three-opamp architecture 170 between a Wheatstone bridge arrangement 172 and the comparator 160 for each channel of the primary sensing layer 104 and the secondary sensing layer 106. Each Wheatstone bridge arrangement 172 receives a differential input signal V in+ and V in- The architecture 170 comprises an input buffer stage 172 followed by a differential amplifier stage 174, after which the signal is conveyed to the comparator 160 so that background noise can be removed from the measurement signal before it is provided to the analog readout circuit 110.

[0057] The input buffer stage 172 and differential amplifier stage 174 are implemented using a three-op amplifier architecture. Two low-noise input amplifiers, A1 and A2, are used for the input buffer stage 172. A third amplifier, A3, is used for the differential amplifier stage 174. As described in more detail below, this architecture achieves high input impedance and excellent linearity and can be configured to extend the input range by using a rail-to-rail input stage.

[0058] A control circuit 112 (e.g., a microprocessor unit) is arranged to generate control signals for the architecture 170. One control signal may be used to set the gain of the input buffer stage 172 through adjustment of a variable resistor R1, which is connected to the control circuit 112 via a digital-to-analog converter (DAC) 176. Similarly, another control signal may be used to set the gain of the differential amplifier stage 174 through adjustment of a variable resistor R3. In the latter case, the output offset of the three operational amplifiers can be adjusted using a digital-to-analog converter (DAC) connected to the input of the fully differential amplifier A3. Thus, the DAC 176 converts the current I P and I N and adjust resistor R3. The control circuit 112 may also generate a common-mode feedback (CMFB) control signal to set the bias current of the differential amplifier stage 174.

[0059] The two input amplifiers A1, A2 may use chopping to eliminate input offset and low frequency flicker noise by means of a chopper switch that enables modulation-demodulation techniques. For example, the two amplifiers A1, A2 in the input buffer stage 172 may be configured to provide a differential input signal V in+ and V in-The differential amplifier stage 174 may have an input chopper switch (not shown) that modulates the amplifier input stage to the chopping frequency, which facilitates up-modulation cancellation of offset and low-frequency flicker noise. Amplifier A3 in the differential amplifier stage 174 may have a chopping output stage configured to reintegrate the signal. The chopping output stage may include a chopper switch configured to synchronously demodulate the signal to its original frequency while modulating the amplifier input stage's offset and 1 / f noise to the chopping frequency. The chopper switches are driven by respective control signals from the microcontroller to implement the appropriate modulation / demodulation process. The chopping frequency is typically selected to be between several hundred Hz and several kHz. The chopping frequency is selected to be greater than (at least twice as large as) the sampling frequency of the ADC 132 to prevent errors due to aliasing.

[0060] A common-mode feedback (CMFB) circuit may be used to maintain the DC voltage output. The CMFB circuit operates to stabilize the common-mode voltage by adjusting the common-mode output current. In this example, the CMFB circuit is configured to detect the common-mode voltage by obtaining the average of the differential output voltage from amplifier A3, compare the obtained average to a reference voltage, and feed the difference voltage between the average and the reference back to the bias network of differential amplifier stage 174. The difference voltage is then converted into a common-mode output current to adjust the common-mode voltage. As a result, it cancels the output common-mode current component and fixes the DC output at the desired level. Typically, the reference voltage may be set to half the rail voltage.

[0061] The transfer function of the proposed three-op-amp structure including the DAC operation is expressed as follows:

[0062]

number

[0063] FIG. 9A is a graph illustrating simulated MMG signals used to simulate the effects of the noise-canceling techniques described above. The graph shows two simulated MMG signals 200, 202 with different amplitudes. The first signal 200 represents the MMG signal near the muscle where it originates. The first signal 200 has a frequency of 100 Hz and an amplitude of 322 pT. The second signal 202 represents the same MMG signal 20 mm further from the muscle than the first signal 200. The second signal 202 has a frequency of 100 Hz and an amplitude of 177 pT to illustrate how the signal attenuates with increasing distance from the muscle. Providing a shielding layer between the TMR sensor in the primary sensing layer 104 and the secondary sensing layer 108 provides further attenuation, with the effect that the MMG signal can be treated as essentially negligible at the TMR sensor in the secondary sensing layer 108.

[0064] 9B is a graph showing the relative magnitude of the noise signal 204 experienced by the TMR sensors in the primary sensing layer 104 and secondary sensing layer 108 compared to the MMG signal 200 near the muscle from which it originates. The noise signal 204 in this example was simulated as a 10 Hz signal with an amplitude of 2.5 μT, an order of magnitude larger than the MMG signal 200. As discussed above with reference to FIG. 6, simulations were performed to apply the inverse of the simulated noise signal in the TMR sensor in the secondary sensing layer 108 to the simulated noise and MMG signal in the TMR sensor in the primary sensing layer 104, demonstrating that the MMG signal can be effectively extracted despite the relatively large amplitude of the noise signal.

[0065] In further embodiments, the noise cancellation techniques described above may be further enhanced by combining the biomagnetic sensor module described herein with an existing bioelectric sensor (e.g., an ECG sensor). The bioelectric sensor provides a complementary sensed output that can be used to remove noise from spectrally similar signals using on-chip signal processing of the biomagnetic signal. In practice, this is accomplished using reservoir computing (RC) techniques, in which the outputs from both the EMG and MMG sensors are analyzed to recognize and separate 1 / f noise from the MMG signal. The use of a physical reservoir computing implementation is beneficial in providing very low training times and memory requirements, as the sensors operate as physical RC model units

[13] .

[0066] To explore the practicality of using the biomagnetic sensor module described above, a model for simulating biomagnetic potentials was established. FIG. 10 shows a cross-section through a representation 400 of muscle tissue 402 used in this simulation model. The image in FIG. 10 shows a cross-sectional area (orthogonal to the fiber direction) of muscle tissue 402, which consists of multiple bundles 404 with multiple fibers 406, 408, 410, each belonging to a different motor unit. Each muscle fiber carries an electric current (a propagating action potential). Based on the different electric currents in each type of muscle fiber, the model simulates the combined effect of magnetic fields generated from time-varying action potentials propagating within a group of skeletal muscle cells in the temporal and spatial domains.

[0067] The layer between the muscle and the skin surface, known as volume conduction, plays an important role during signal measurement. Finite-difference time-domain simulations were obtained using the simulation model described above to study the volume conduction effect on electrical and magnetic signals. Figure 11A shows a cross section through a representation of muscle tissue 500, showing the simulated electric field potential within a volume 501 between a muscle bundle 505 and the skin surface 507 in the absence of a fat layer. Figure 11B shows the same cross section, but with the simulated magnetic field potential.

[0068] Figure 11C shows a cross section through another view of muscle tissue showing simulated electric field potentials within a volume 501 between muscle fiber bundles 505 and the skin surface 507, with a fat layer 503 around the muscle fiber bundles. Figure 11D shows the same cross section, but with simulated magnetic field potentials.

[0069] Figure 12 is a graph showing the simulated electric field potential variation through lines AA and CC in Figures 11A and 11C. Figure 13 is a graph showing the simulated magnetic field potential variation through lines BB and DD in Figures 11B and 11D. From the inset in Figure 12, it can be seen that adding a 1 mm fat layer reduces the electrical signal 502 by 60% compared to the electrical signal 504 at the skin surface, but the magnetic field potential remains unchanged. Thus, the layer separating the skin and the signal source is transparent to the magnetic field but acts to perturb the electric field.

[0070] Figure 14 is a graph showing the variation of biomagnetic potential with distance from its source in muscle tissue. The graph was obtained using the simulation model described above. It can be seen that the magnitude of the biomagnetic potential drops off rapidly from the source, already approaching 50 pT at the skin surface. However, in the zone 25–30 mm from the source (10–15 mm from the skin surface), the magnitude of the biomagnetic field is in the range of 24–28 pT, which is within the sensitivity range of the TMR sensor described above. Because the magnetic field magnitude is still reduced in this detection zone, the secondary sensing layer experiences a significantly lower biomagnetic field. As described with respect to Figure 1, providing a shielding layer between the primary and second sensing layers ensures that the biomagnetic field is negligible at the secondary sensing layer.

[0071] As explained above, the biomagnetic sensing device of the present invention can use a combination of different techniques to cancel noise in the environment (i.e., the Earth's magnetic field, thermal and 1 / f noise): 1) Readout circuit techniques such as chopping and auto-zeroing to compensate for offsets 2) On-chip gradiometer integration using a separate TMR sensor to record the Earth's magnetic field 3) Use of a thermally stable material layer at the device manufacturing level to stabilize the temperature.

[0072] The features disclosed in the foregoing description, or the following claims, or the accompanying drawings, are expressed in their specific form, or in terms of means for performing a disclosed function, or methods or processes for obtaining a disclosed result, and may, where appropriate, be utilized separately or in any combination of such features to realize the invention in various of its forms.

[0073] While the present invention has been described in conjunction with the above exemplary embodiments, many equivalent modifications and variations will be apparent to those skilled in the art given this disclosure. Accordingly, the above exemplary embodiments of the present invention are considered to be illustrative and not limiting. Various changes to the described embodiments can be made without departing from the spirit and scope of the invention.

[0074] For the avoidance of doubt, any theoretical explanations provided herein are provided for the purpose of improving the understanding of the reader, and the inventors do not wish to be bound by any of these theoretical explanations.

[0075] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described.

[0076] Throughout this specification, including the claims which follow, unless the context requires otherwise, the words "comprise" and "include," and variations such as "comprises," "comprising," and "including," are understood to mean the inclusion of a stated integer or step or group of integers or steps, but not the exclusion of any other integer or step or group of integers or steps.

[0077] It should be noted that as used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Ranges may be expressed herein as from "about" one particular value and / or to "about" another particular value. When such a range is expressed, another embodiment includes from the one particular value and / or to the other particular value. Similarly, when values ​​are expressed as approximations, by use of the antecedent "about," it will be understood that the particular value forms another embodiment. The term "about" with respect to numerical values ​​is optional and means, for example, ±10%.

[0078] References Several publications are cited above in order to more fully describe and disclose the present invention and the art to which it pertains. Full citations for these references are provided below. Each of these references is incorporated herein in its entirety.

[0079] [1] J. Malmivuo and R. Plonsey, Bioelectromagnetism: principles and applications of bioelectric and biomagnetic fields. Oxford University Press, USA, 1995. [2] DBGeselowitz, 'Magnetocardiography: an overview', IEEE Transactions on Biomedical Engineering, no. 9, pp. 497-504, 1979. [3] R. Fenici, D. Brisinda, and AMMeloni, 'Clinical application of magnetocardiography', Expert Review of Molecular Diagnostics, vol. 5, no. 3, pp. 291-313, 2005. [4]S.Baillet,‘Magnetoencephalography for brain electrophysiology and imaging’,Nature Neuroscience,vol.20,no.3,pp.327-339,2017. [5]E.Boto et al.,‘Moving magnetoencephalography towards real-world applications with a wearable system’,Nature,vol.555,no.7698,p.657,2018. [6]S.Zuo,H.Heidari,D.Farina,and K.Nazarpour,‘Miniaturized magnetic sensors for implantable magnetomyography’,Advanced Materials Technologies,no.2000185,2020. [7]S.Zuo et al.,‘Ultrasensitive Magnetoelectric Sensing System for pico-Tesla MagnetoMyoGraphy’,IEEE Transaction on Biomedical Circuits and Systems,2020. [8]B.-M.Mackert,‘Magnetoneurography:theory and application to peripheral nerve disorders’,Clin.Neurophysiol.,vol.115,no.12,pp.2667-2676,2004. [9]C.-H.Im,S.C.Jun,and K.Sekihara,‘Recent advances in biomagnetism and its applications’.Springer,2017.

[10] R.Kleiner,D.Koelle,F.Ludwig,and J.Clarke,‘Superconducting quantum interference devices:State of the art and applications’,Proceedings of the IEEE,vol.92,no.10,pp.1534-1548,2004.

[11] S.Zuo,K.Nazarpour,and H.Heidari,‘Device modelling of MgO-barrier tunnelling magnetoresistors for hybrid spintronic-CMOS’,IEEE Electron Device Letter,vol.39,no.11,pp.1784-1787,2018.

[12] H.Heidari,S.Zuo,A.Krasoulis,and K.Nazarpour,‘CMOS Magnetic Sensors for Wearable Magnetomyography’,2018 40th International Conference of the IEEE Engineering in Medicine and Biology Society(EMBC),Honolulu,HI,2018,pp.2116-2119.

[13] Liang,X.,Zhong,Y.,Tang,J.et al.Rotating neurons for all-analog implementation of cyclic reservoir computing.Nat Commun 13,1549(2022).

Claims

1. a tunneling magnetoresistive TMR sensor unit configured to output a detection signal indicative of a magnetic field adjacent to biological tissue; a gradiometer unit configured to output a background signal indicative of ambient magnetic noise; a shielding element disposed between the TMR sensor unit and the gradiometer unit; an active noise cancellation unit configured to remove the background signal from the detection signal to generate a biomagnetic signal; an analog readout circuit configured to receive the biomagnetic signal and perform signal conditioning to produce an analog output; an analog-to-digital converter ADC arranged to generate a digital output signal from said analog output; A biomagnetic sensor module comprising:

2. The biomagnetic sensor module of claim 1 , wherein the gradiometer unit comprises a three-axis gradiometer.

3. The biomagnetic sensor module of claim 1 or 2, wherein the gradiometer unit comprises a plurality of TMR sensors configured to detect ambient magnetic noise.

4. 10. The biomagnetic sensor module according to any of the preceding claims, wherein the TMR sensor unit comprises four TMR sensors in a Wheatstone bridge arrangement.

5. 10. The biomagnetic sensor module of any preceding claim, wherein the TMR sensor unit is one of a plurality of similarly configured TMR sensor units, each TMR sensor unit arranged to detect a magnetic field adjacent biological tissue and output a biomagnetic signal on a respective channel, and wherein the biomagnetic sensor module further comprises a multiplexer configured to selectively couple each respective channel to the analog readout circuitry.

6. 10. The biomagnetic sensor module of any of the preceding claims, further comprising a skin contact interface made from a biocompatible material.

7. The biomagnetic sensor module of claim 6 , wherein the gradiometer unit is positioned farther from the skin contact interface than the TMR sensor unit.

8. 10. The biomagnetic sensor module of any preceding claim, wherein the shielding element comprises a magnetically permeable material.

9. 10. The biomagnetic sensor module of any of the preceding claims, further comprising a compensation unit configured to minimize baseline mismatch between the TMR sensor unit and the gradiometer unit.

10. 10. The biomagnetic sensor module of claim 9, wherein the compensation unit comprises a feedback circuit configured to receive a baseline output from the TMR sensor and a gradiometer unit and adjust the gradiometer unit to minimize the baseline output.

11. 11. The biomagnetic sensor module of claim 9 or 10, wherein the compensation unit comprises an adjustable current source configured to generate a bias signal for the gradiometer unit, the bias signal being adjustable to minimize the baseline output.

12. 11. The biomagnetic sensor module of claim 9 or 10, wherein the compensation unit comprises a variable gain amplifier connected between the gradiometer unit and the active noise cancellation unit, the gain of the variable gain amplifier being adjustable to minimize the baseline output.

13. 10. The biomagnetic sensor module of claim 1, wherein the TMR sensor unit is disposed in a primary sensing layer and the gradiometer unit is disposed in a secondary sensing layer parallel to and spaced apart from the primary sensing layer.

14. The biomagnetic sensor module of claim 13 , wherein the primary sensing layer is spaced from the secondary sensing layer by a distance of 10 mm or less.

15. 15. The biomagnetic sensor module of claim 13, wherein the active noise cancellation unit and the analog readout circuit are disposed in one or more layers parallel to and spaced apart from the secondary sensing layer.

16. 10. The biomagnetic sensor module of any of the preceding claims, wherein the analog read circuit comprises a band-pass filter and a common-mode feedback circuit.

17. 10. The biomagnetic sensor module of any of the preceding claims, further comprising a wireless communication unit configured to transmit said digital output signal to a remote device.

18. A wearable biomagnetic sensing device comprising a biomagnetic sensor module according to any one of the preceding claims.

19. 19. A wearable biomagnetic sensing device according to claim 18, comprising a plurality of biomagnetic sensor modules according to any one of claims 1 to 17 fixed to a holding element wearable on a human body.

20. The wearable biomagnetic sensing device of claim 19 , wherein the retaining element is an elastic strap.

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