My research focuses on the design of bio-inspired integrated micro-electronic technology for application in healthcare. It is underpinned by the following principal areas:
Bio-inspired design: This involves designing systems by taking inspiration from biology to replicate bio-inspired processing and decision-making to create more efficient medical devices.
Integrated Sensing Systems: This involves integrating sensing modalities within available CMOS technology allowing the design of lab-on-chip devices, which fully integrate chemical sensors, low-power instrumentation and processing algorithms which are completely scalable to multiplex millions of sensors.
Novel Medical devices: This involves utilising the knowledge of bio-inspired design, integrated sensing and microelectronic technology to make medical devices which address current challenges in healthcare.
Applying these, I am currently focusing on solving the following healthcare related challenges:
Management of Diabetes: Diabetes is described by the body’s inability to control blood glucose which is typically treated by insulin injection to lower blood glucose. However, the non-automated nature of control leads to severe complications such as blindness and heart disease and can be dangerous through inducing hypoglycaemia. Recognising the need for a treatment for diabetes through a fully automated system and the impact it will have, my group is working on:
- The Bio-inspired Artificial Pancreas: This involves research into creating a fully closed-loop system using microelectronic technology which replicates the way the beta-cells of the pancreas work to automatically control blood glucose through continuous infusion of insulin. Support: The Wellcome Trust.
- Adaptive Decision Support Systems: Recognising that diabetes management is affected by many lifestyle related parameters such as exercise, stress and illness, my group is researching adaptive decision support systems using artificial intelligence techniques which utilise wearable technology to improve diabetes control. Support: EPSRC, Industry (Dexcom Ltd).
- More info: http://www.imperial.ac.uk/bio-inspired-technology/research/metabolic/
Control of infection and antimicrobial resistance: Infectious disease is a widespread problem both in UK hospitals and in developing countries. There is an urgent need for diagnostic tools able to accurately identify infections at the point of care to ensure timely and targeted clinical management. This is especially important for infection control in low-middle income countries where access to healthcare facilities is limited and during pandemics such as COVID-19. Towards this, my group is working on:
- Infection Technology: This involves research into creating rapid, highly sensitive and affordable Lab-on-Chip diagnostics using CMOS integrated sensing technology. These can identify pathogens using molecular methods involving DNA/RNA detection, leading to rapid response for infection control. Currently we are working with developing countries (Thailand, Vietnam, Ghana, South Africa) to create platforms for detection of Dengue, TB, Malaria and with the UK-NHS for bacterial infection to control AMR in addition to addressing COVID-19. Support: NIH, EPSRC, H2020, Rosetrees Trust, The Wellceome Trust.
- Decision support systems for Antibiotic prescribing: This involves the use of artificial intelligence for clinical decision support in antimicrobial prescribing. This is to optimise prudent antimicrobial prescribing, using software-based systems within hospitals. Support: NIHR, EPSRC.
- More info: http://www.imperial.ac.uk/bio-inspired-technology/research/infection-technology/
Management of chronic conditions using wearables: Utilisation of wearable technology for continuous monitoring of physiological parameters can lead to improvements in chronic conditions in addition to providing predictive factors for onsets of conditions and alarms. There are several technological challenges however which need to be addressed which include integration, power consumption, data transmission and accuracy in measurement. Towards this, my group is researching fully integrated wearables using CMOS technology for Osteoarthritis, muscle fatigue monitoring and metabolite monitoring through skin and sweat. Support: EPSRC.
- More Info: Wearable Muscle Fatigue Monitor
My Student Awards
Mr Priyank Hirani, MSc - Awarded the EEE Prize for Outstanding Achievement in Analogue and Digital IC design, Project "A Low Power Multi-channel Glucose Sensing System ".
Miss Jean Weatherwax, MSc - Awarded the Hertha Ayrton Centenary Prize for best MSc project with significant original contibution, Project "A Self-Calibrating Sensing Array for Continuous Glucose Monitoring in Diabetes ".
Mr Nicholaos Miscourides - Awarded the Sir Bruce White Prize in Electrical Engineering for the best final year Project, Project "Semiconductor Genetic Sequencing Using Ion-Sensitive Field Effect Transistors".
Mr Connel Hepburn - Awarded the Nujira Prize for outstanding achievement in analogue electronics, Project "Wireless control of blood glucose for diabetes in the clinical ward".
Mr Nicolas Moser MSc - Awarded the EEE Prize for Outstanding Achievement in Analogue and Digital IC design and Awarded the Hertha Ayrton Centenary Prize for best MSc project with significant original contibution, Project "An ISFET based DNA sequencing system with pixel compensation".
Mr Jack Heaffey MEng - Awarded the EEE prize for the best MEng project entitled "A Wearable Device for Muscle Fatigue Detection in Rehabilitation of Athletes."
Mr Yaoxing Hu MEng - Awarded the Eric Laithwaite Prize for the most innvovative final year project entitled "Self-calibrating Multi-channel Continous Glucose Monitoring System".
Mr Guenole Lallement MSc - Awarded the Hertha Ayrton Centenary Prize for best MSc project with significant original contibution, Project "Bio-inspired pH sensing using Ion Sensitive Field Effect Transistors".
Mr Ahmad Moniri - Awarded the Governors' MEng Prize in Electrical & Electronic Engineering for outstanding contribution, Project "Novel Algorithms and Models for Sensing DNA through ISFET arrays".
Mr Prateek Tripathi, MSc - Awarded the prize for Outstanding Achievement in the Analogue and Digital Integrated Circuit Design Master of Science, Project "A Brain-inspired ISFET Array".
Mr Taiyu Zhu, MSc - Awarded the prize for Outstanding Achievement in the Communications and Signal Processing Master of Science, Project "A smartphone-based platform integrating AI for adaptive glucose prediction".
Microchip Technology enabling rapid diagnostics : from AMR - COVID-19, Institute for Molecular Science and Engineering, Imperial College London, 2021
CMOS Ion-Sensing Arrays enabling Rapid Diagnostics and Surveillance for COVID-19, IEEE Solid States Circuits conference (ISSCC) special event ‘Silicon Technologies in the fight against pandemic, IEEE, 2021
Tutorial - Microelectronics for DNA detection: From Sensors to Rapid Diagnostic Systems using CMOS Ion-Sensitive Field Effect Transistors’, IEEE International Symposium on Circuits and Systems 2020, 2020
Creating a Hand Held Test for COVID -19, Imperial College Lock Down Lessons, Imperial College London, 2020
Microchip Technology enabling Rapid Diagnostics and Surveillance of COVID-19, Friends of Imperial College, 2020
Microchip Technology enabling Rapid Diagnostics for Infectious Diseases – Addressing COVID-19, Imperial Global Science Policy Forum, Imperial College London, 2020
Microchip Technology enabling Rapid Diagnostics and Surveillance of COVID-19, University of Leeds, Leeds, 2020
Microchip Technology enabling rapid diagnostics for infectious diseases, IEEE UKCAS, London, 2019
Optimising antimicrobial use through Technology and Artificial Intelligence, Institute of Global Health Innovation, Imperial College London, 2019
Microchip Technology enabling rapid diagnostics for infectious diseases, Imperial College London, Technical Solutions to Support Infection Management and Address Antimicrobial Resistance, White City, 2019
CMOS Microelectronics for DNA detection using Ion-Sensitive Field Effect Transistors, IEEE SWISS CASS TALK, ETH, Zurich, Switzerland, 2019
CMOS Microelectronics for DNA detection using Ion-Sensitive Field Effect Transistors, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland, 2019
CMOS Microelectronics for DNA detection using Ion-Sensitive Field Effect Transistors., Nagoya University, Nagoya, Japan, 2019
Microchip Technology enabling rapid diagnostics for infectious diseases, Imperial College London, All You Can Innovate 2019, Imperial College London, 2019
Bio-inspired AI is revolutionising healthcare, The Economist - The Artificially Intelligent Healthcare Sector, Athens, Greece, 2019
Bio-inspired microelectronics for improving human health, IEEE International Symposium on Medical Measurements and Applications 2018, Rome, Italy, 2018
Microelectronics for Infectious Diseases using Ion-Sensitive Field Effect Transistors, University of Manchester, Manchester, UK, 2018
Microelectronics for Infectious Diseases using Ion-Sensitive Field Effect Transistors, SMART NUS Singapore, Singapore, 2018
CMOS microelectronics for DNA detection in Infectious Diseases, NTU, Singapore, Singapore, 2018
The bio-inspired artificial pancreas for treatment of diabetes in the home, ARM, ARM, Cambridge, 2018
Microchip diagnostics for malaria species and resistance detection, UK Parliament, UK Parliament, Westminster, 2018
CMOS Microelectronics for DNA detection using Ion-Sensitive Field Effect Transistors, Department of Electronic Engineering, University of York, York, 2018
CMOS Microelectronics for DNA detection using Ion-Sensitive Field Effect Transistors., Newcastle University, Newcastle, UK, 2017
The bio-inspired artificial pancreas for treatment of diabetes in the home, New York University, Abu Dhabi, Abu Dhabi, 2017
CMOS Microelectronics for DNA detection using Ion-Sensitive Field Effect Transistors, Department of Electrical Engineering, University of Cape Town, University of Cape Town, Rondebosch, South Africa, 2017
The bio-inspired artificial pancreas for treatment of diabetes in the home, 2017 Sensors in Medicine Conference, London, 2017
Microchip diagnostics for malaria speciesand resistance detection, Imperial College, Networks of Excellence in Malaria Launch, 2017
CMOS Microelectronics for DNA detection using Ion-Sensitive Field Effect Transistors, IEEE Distinguished Lecturer Talk, Taiwan, 2017 VLSI/CAD Conference, Kenting, TaiwanNTU, TaipeiNTHU, HsinchuNCKU, Tainan, 2017
Microchip Technology Enabling Rapid Diagnostics for Infectious Disease, Imperial AHSC, Royal Brompton Hospital, 2017
Keynote: Bio-inspired Microchips for Improving Human Health, IEEE NEWCAS conference 2017, Strasbourg, France, 2017
The Bio-inspired Artificial Pancreas for treatment of diabetes in the home, DATE 2017 Conference, EPFL, Lausanne, Switzerland, 2017
CMOS Design for DNA detection using Ion-‐Sensitive Field Effect Transistors, IEEE Sensors Summer School, EPFL, Lausanne, Switzerland, 2016
A Bio-inspired Artificial Pancreas for treatment of diabetes, University of Toronto, Toronto, Canada, 2016
A Bio-inspired Artificial Pancreas for treatment of diabetes, Imperial Medtech on wearables, behaviour and data, Imperial College London, UK, 2016
Microchip diagnostics for AMR, University of York, York, UK, 2015
Engineering, Physical, Natural Sciences and Medicine Bridging Research in Antimicrobial resistance: Collaboration and Exchange, University of Southampton, Southampton, UK, 2015
Diabetes treated by a microchip!, The Institution of Engineering and Technology - The IET, Portsmouth, 2015
Bio-inspired Semiconductors for Healthcare, IEEE UK and Ireland Section public keynote talk, 2014
Implanted circuitry inspired by human engineering, Institute of Physics, London, 2014
Bio-inspired Semiconductors in Healthcare, Institute of Physics, University of Kent, 2014
The bio-inspired artificial pancreas for treatment of diabetes., Westminster School, Westminster SchoolThe Robert Hooke Science Centre7 - 9 Dean Bradley StreetLondon SW1P 3EP, 2012
Research Student Supervision
Afentakis,I, Machine Learning Algorithms for Diabetes Management (2020-)
Beykou,M, Novel Bio-Chips for real-time detection of acidification in the tumour microenvironment (2020-)
Bolton,W, Addressing multi-morbidity in the NHS: Optimising antibiotic therapy in obesity using intelligent, personalised clinical decision support systems (2020-)
Broomfield,J, Development of a Lab-on-Chip System for Detection and Quantification of Circulating mRNA in Prostate Cancer (2020-)
Cacho Soblechero,M, Digital Chemical Pixel: A sense-aware ISFET array for PoC applications (2017-)
Cicatiello,C, A portable microfluidic platform for real-time detection of secondary brain injuries through an electrochemical multi-ion imaging. (2019-)
Daniels,J, Multimodal Machine Learning for Diabetes Management (2017-)
Douthwaite,M, Using CMOS Lab-on-a-chip Technology to Monitor Physiology through Remote, Continuous and Unobtrusive Analysis of Perspiration (2016-2020)
Guemes Gonzalez,A, NeuMedic: Neuromodulated Diabetes Control (2017-2020)
Hernandez,B, Data-driven web-based intelligent decision support system for infection management at point of care Enhancing approaches to antimicrobial stewardship (2015-2018)
Hu,Y, Advanced sensing and processing methodologies for ISFET based DNA sequencing (2011-2015)
Karolcik,S, PPG-based wearable system for the prediction of Dengue complications (2018-)
Keeble,L, Actuation of DNA using AC Electric Fields to Provide a Signal Boost for ISFET-based Detection (2018-)
Koutsos,E, A low-power real-time sEMG ASICs for muscle fatigue monitoring (2013-2016)
Ma,J, Monolithic Integration of Wireless Electrochemical Sensors (2018-)
Malpartida Cárdenas,K, Development of rapid point-of-care diagnostics to tackle drug-resistant malaria (2017-)
Miscourides,N, Linear ISFET arrays and optimisation methods for DNA detection (2014-2019)
Moniri,A, Multidimensional diagnostics for rapid detection of infectious diseases (2017-2021)
Moser,N, Integrated auto-calibration and in-pixel quantisation methodologies for CMOS ISFET arrays in Point-of-Care diagnostics (2014-2018)
Panteli,C, Graphene Inspired Sensing Devices (2015-2019)
Pennisi,I, Translation of Gene Expression Signatures into a Point-of-care-Test (2017-)
Pesl,P, An Intelligent Decision Support System for Improved Insulin Dosing (2011-2016)
Rawson,T, Enhancing approaches to antimicrobial stewardship (2015-2018)
Sharkawy,ME, Bio-inspired methods for control of diabetes. (2011-2016)
Srtinger,O, Development of a point-of-care diagnostic for pathogens involved in the porcine respiratory disease complex (2019-)
Terracina,D, Monitoring muscle fatigue using novel wireless sensors (2018-)
Zeng,J, High Speed Ion Imagers (2018-)
Zhu,T, Deep Learning Algorithms for Diabetes Management (2019-)