I aim to promote and support engineering and physical science research in different sensors and microelectronics design. My research is broadly ranging from theoretical, simulation, design, fabrication and experimental work in fundamental physics to applications of wearable and implantable electronics. I am working on an ambitious project of developing a new technological tool based on a wireless and implantable spintronic sensor for the detection of three-dimensional magnetic fields from the skeletal muscles. My long-term vision is to transform the diagnosis of peripheral muscle and nerve diseases and to radically enhance the efficacy of motor rehabilitation after stroke, spinal cord injury or limb loss. A key challenge remained over the past four decades is the development of effective methods for the measurement of muscle activity that offer high spatial and temporal resolutions. Conventionally, muscle activity can be recorded and analysed electrically by electromyography method from the surface of the skin using metal electrodes, which is a well-established method and widely used today in basic, sports and clinical studies. However, the surface electric signals suffer from poor spatial resolution. It is difficult, if not impossible, to record from individual motor units within a muscle selectively. High-density needle electrodes are even utilised to target specific tissues. In addition to being painful, the penetration of the needle into the muscle disturbs the muscle structure and function. Moreover, in chronic implants, such as for the motor rehabilitation, the interface between the metal contacts of the sensor and the human tissue changes over time, leading to infection and rejection by the body. Thus, there is an urgent need for an innovative alternative paradigm that enables the recording of muscle activity at high spatial resolution with minimal invasiveness. Biomagnetism, which is the magnetic counterpart of bioelectricity method, is the only conceivable candidate that can address both limitations target objectives. I aim to develop and validate, for the first time, a wireless implantable spintronic-based system. It will integrate readout microelectronic circuit and function in a sub-pico-Tesla range at room temperature. Addressing the technical challenges in an unprecedented level of miniaturization, the sensor detection range with their wireless power and data transfer can enable the use of chronic magnetic signals recording for a wide range of applications in movement neuroscience, in the diagnosis of peripheral muscle and nerve diseases, and in technologies for motor rehabilitation.
Magnetic-based medical systems are using widely for sensing and imaging applications ranging from magnetic biosensors to magnetic resonance imaging and nuclear magnetic resonance. Magnetomyography (MMG) is an efficient and robust method for human-machine interface applications to control the prosthetic and robotics hands through record small magnetic fields produced by the electrical activity of skeletal muscles. 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. In our article 2000185 at Advanced Materials Technologies, we propose a new concept for miniaturized MMG to analysis of muscle function through the inquiry of the generated magnetic signal. The high sensitivity of multilayered spintronic sensors based on tunnelling magnetoresistive (TMR) sensors, in range of pico-Tesla, makes them particularly a promising technology for miniaturized wearable and implantable applications.
Lab-on-a-Chip Malaria Diagnostics
We chose to create an innovative device that addresses one of today’s deadliest diseases. Malaria is a life-threatening condition that continues to afflict millions of people worldwide. Traditional methods of diagnosing malaria can prove to be time consuming, complex and require a great level of expertise. These characteristics are often a key limitation in malaria-affected regions that lack medical resources. Through this project, we were able to contribute to the growing efforts of creating a simple, affordable and portable diagnostic device.
A distinctive feature of malaria-infected red blood cells is the presence of the malaria pigment called hemozoin. Hemozoin is a paramagnetic substance that has a magnetic moment only in the presence of an applied magnetic field. Our device consists of a Tunnelling Magneto-resistive (TMR) sensor, magnetic Halbach array, analogue front-end circuit for filtering, ADC and PC interface to display the sensor output. Our device can effectively detect a paramagnetic sample and display a clean output on the LabVIEW (a graphical programming tool) interface which can then be read by the end-user to diagnose malaria-infected patients. ur team worked effectively and drew on their diverse strengths to realise this project. Our research, preparation, and consistent efforts allowed us to explore and implement new ideas.
Human Brain-Machine Interface
Hybrid Enhanced Regenerative Medicine Systems (HERMES) consortium is joining their efforts to establish a new paradigm in regenerative medicine, aiming at overcoming the biological uncertainty inherent to it. This paradigm is named enhanced regenerative medicine and it is rooted in the establishment of biohybrid neuronics (neural electronics), that is the symbiotic integration of bioengineered brain tissue, neuromorphic microelectronics and artificial intelligence. Therefore, HERMES pursues the long-term vision of healing disabling brain disorders by means of brain tissue transplants, a reality that is only possible to date for other organs of the human body.
At University of Glasgow, we are developing miniaturized biocompatible devices and microelectronics on neural interfaces from fundamental physics to wide applications of wearable and implantable electronics. Besides, we are working on the next generation highly sensitive devices & flexible microelectronics, including theoretical analysis, computational modelling and simulation, design, and fabrication.
Sonomyography (SMG) refers to the measurement of muscle activity with an ultrasonic transducer. It is a candidate modality for applications in diagnosis of muscle conditions, rehabilitation engineering and prosthesis control as an alternative to electromyography. In this project, we propose a mechanically-flexible piezoelectric SMG sensor. Through simulating different components of the transducer, using COMSOL Multiphysics software, we analyze various electromechanical parameters, such as von Mises stress and charge accumulation. Our findings on modelling of a single-element device, comprised of a PZT-5H layer of thickness 66µm, with a polymer substrate (E = 2.5 GPa), demonstrate optimal flexibility and charge accumulation for sonomyography. The addition of Polyimide and PMMA as an acoustic matching layer and an acoustic lens, respectively, allowed for adequate energy transfer to the medium, whilst still maintaining good mechanical properties. In addition, preliminary ultrasound transmission simulations (200 kHz-30 MHz) showed the importance of the aspect ratio of the device and how there is a need for further studies on it. The development of such a technology could be of great use within the healthcare sector, not only due to its ability to provide highly accurate and varied real-time muscle data, but also because of the range of applications that could benefit from its use.
The surface mechanomyogram (MMG) (detectable at the muscle surface as MMG by accelerometers, piezoelectric contact sensors or other transducers) is the summation of the activity of single motor units (MUs). Each MU contribution is related to the pressure waves generated by the active muscle fibres. The MMG has been extensively applied in clinical and experimental practice to examine muscle characteristics including muscle function (MF), prosthesis and/or switch control, signal processing, physiological exercise, and medical rehabilitation. Despite several existing MMG studies of MF, there has not yet been a review of these. This study aimed to determine the current status on the use of MMG in measuring the conditions of MFs.
Electromyography (EMG) is a standard technology for monitoring muscle activity in laboratory environments. An alternative muscle monitoring technique, MMG differs from EMG in that it measures the low-frequency (2 - 200 Hz) mechanical response of the lateral oscillation of muscle fiber during contraction. The research suggests that the frontalis muscle is a suitable site for controlling the MMG-driven switch. The high accuracies combined with the minimal requisite effort and training show that MMG is a promising binary control signal. Further investigation of the potential benefits of MMG-control for the target population is warranted.
Smart Wearable Sensing Devices
The conventional wearable devices approach to date has been to encode the arriving signals, e.g. time of flight of the photons using high precision counters for each single-photon avalanche diode (SPAD) cell and to transfer this data off-chip for processing. This approach typically involves as a first step some form of averaging over a large number of frames which effectively removes the possibility of on-chip processing. Thus, this transfer process also creates an information bottleneck which is currently one of the major limiting factors in the speed of operation of sensors. Besides, the use of conventional CPU & GPU for processing this temporal data makes processing data computationally intensive using conventional signal processing techniques and results in significant power & hardware requirements. In addition, to diagnose and manage high blood pressure, it is important to measure blood pressure routinely.
This project will engineer a low-power wearable device consists of electrocardiography (ECG) and photoplethysmography (PPG) sensors with on-chip neuromorphic sensing processor. Given the potential of the ECG + PPG system with machine learning, the main concerns are the power, accuracy and computing efficiency. Such novel multi-sensory architecture and high learning ability usually require more power in the wearable computing unit. Traditional solutions mostly pursued the trade-off between power duration and computing capability. In this project, we proposed a neuromorphic processor for the fusion of PPG and ECG, and cognitively processing both signals. Based on our existing experience on sensor, microelectronic design and neuromorphic processor, this project aims to remove energy-hungry digital components and use fully analogue neuromorphic building blocks instead. The expected processor will significantly reduce the power and large volumes of noisy and largely redundant spatiotemporal data as well as increase speed of biomedical wearable devices.
Micro-NMR CMOS Integrated Platform
This project presents a micro-nuclear magnetic resonance (NMR) system compatible with multi-type biological/chemical lab-on-a-chip assays. Unified in a handheld scale (dimension: 14 x 6 x 11 cm³, weight: 1.4 kg), the system is capable to detect < 100 pM of Enterococcus faecalis derived DNA from a 2.5 μL sample. The key components are a portable magnet (0.46 T, 1.25 kg) for nucleus magnetization, a system PCB for I/O interface, an FPGA for system control, a current driver for trimming the magnetic (B) field, and a silicon chip fabricated in 0.18 μm CMOS. The latter, integrated with a current-mode vertical Hall sensor and a low-noise readout circuit, facilitates closed-loop B-field stabilization (from 2 mT → 0.15 mT), which otherwise fluctuates with temperature or sample displacement.
Together with a dynamic-B-field transceiver with a planar coil for micro-NMR assay and thermal control, the system demonstrates: 1) selective biological target pinpointing; 2) protein state analysis; and 3) solvent-polymer dynamics, which is suitable for healthcare, food and colloidal applications. Compared to a commercial NMR-assay product (Bruker mq-20), this platform greatly reduces the sample consumption (120x), hardware volume (175x), and weight (96x).
Miniaturized Magnetic Sensors for Biomedical and Healthcare Applications
Miniaturized Magnetoresistive (MR) Sensor Array
Tunnel magnetoresistance (TMR) is a magnetoresistive effect that occurs in a magnetic tunnel junction (MTJ), which is a component consisting of two ferromagnets separated by a thin insulator. If the insulating layer is thin enough (typically a few nanometres), electrons can tunnel from one ferromagnet into the other. The tunnel magnetoresistance is a strictly quantum mechanical phenomenon.
Magnetoelectric (ME) Sensors
Magnetoelectric (ME) effect is characterized by appearance of an electric polarization (P) tempered by a magnetic field (H) or vice-versa. There are various types of piezoelectric (PE) and piezo magnetic (PM) materials and combination of which can lead to excellent ME effect.
High-Precision & Low-Noise Biomagnetic Measurement Circuits and Systems
High-Precision Biomagnetic Measurement System Based on Tunnel Magneto-Resistive Effect: This project presents a novel low-noise and high-precision readout circuit for tunnelling magnetoresistive (TMR) array to evaluate the suitability of biomagnetic measurement platform for detection of weak biomagnetic fields. We propose a three operational-amplifier architecture with a high input impedance and an adjustable gain for the fabricated TMR sensor that is highly miniaturized and can be operated at room temperature. The proposed system was designed using standard 0.18 μm CMOS technology and achieved a good performance with regard to gain, linearity, power consumption, and noise by employing a chopper stabilization technique and common mode feedback. The gain can reach 80 dB through adjusting two 5-bit programmable resistors and the input-referred noise voltage only has 44.6 nV/√Hz with 10 nA input bias over a wide range of frequency. Moreover, the whole readout dissipates 58 μW of power with a 1.8 V supply voltage. Benefiting from the CMOS compatibility of the TMR sensor, it offers monolithic integration directly on a silicon substrate as a TMR-on-chip sensing system. This will enable a new scientific and engineering paradigm to revitalize the biomagnetism field as an alternative way to understand the underlying mechanism of the human body.