Publications
410 results found
Hu Y, Moser N, Georgiou P, 2017, A 32 x 32 ISFET Chemical Sensing Array With Integrated Trapped Charge and Gain Compensation, IEEE SENSORS JOURNAL, Vol: 17, Pages: 5276-5284, ISSN: 1530-437X
This paper presents a CMOS-based 32 × 32 ion-sensitive field-effect transistor (ISFET) system-on-chip for real-time ion imaging. Fabricated in an unmodified 0.35-μm CMOS technology, the ISFET sensor array is based on a pixel topology, which uses capacitive feedback to improve signal attenuation due to passivation capacitance and a low-leakage floatinggate reset followed by a digital correlated double sampling to robustly remove unwanted trapped charge-induced dc offset. An automatic gain calibration (AGC) is used to perform realtime calibration and guarantee all sensors that have the same gain with a 99% accuracy, and combining all these mechanisms guarantees an average pixel voltage variation of 14.3 mV after gain is applied when measured over multiple dies. The full array is experimentally shown to be capable of real-time ion imaging of pH, with an intrinsic sensitivity of 39.6mV/pH and a scan rate of 9.3 frames/s when running the AGC, with a total power consumption of 10.2 mW.
Panteli C, Georgiou P, Fobelets K, 2017, Optimising the performance of commercial ISFET sensors using Reactive Ion Etching, MNE 2017
Herrero Vinas P, Pesl P, Reddy M, et al., 2017, Atomatic adjustment of Basal insulin infusion rates in type 1 diabetes using run-to-run control and case-based reasoning, Artificial Intelligence in Medicine
People with type 1 diabetes mellitus rely on a basal-bolus insulinregimen to roughly emulate how a non-diabetic person’s body delivers insulin.Adjusting such regime is a challenging process usually conducted by an expertclinical. Despite several guidelines exist for such purpose, they are usuallyimpractical and fall short in achieving optimal glycemic outcomes. Therefore,there is a need for more automated and efficient strategies to adjust such regime.This paper presents, and in silico validates, a novel technique to automaticallyadapt the basal insulin profile of a person with person with type 1 diabetes. Thepresented technique, which is based on Run-to-Run control and Case-BasedReasoning, overcomes some of the limitations of previously proposedapproaches and has been proved to be robust in front of realistic intra-dayvariability. Over a period of 5 weeks on 10 virtual adult subjects, a significantreduction on the percentage of time in hyperglycemia (<70mg/dl) (from 14.3±5.6to 1.6±1.7, p< 0.01), without a significant increase on the percentage of time inhypoglycemia (>180mg/dl) (from 10.2±5.9 to 1.6±1.7, p=0.1), was achieved.
Moser N, Leong CL, Hu Y, et al., 2017, Live Demonstration: Real-Time Chemical Imaging of Ionic Solutions Using an ISFET Array, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
Xiao W, Miscourides N, Georgiou P, 2017, A Novel ISFET Sensor Architecture using Through-Silicon Vias for DNA Sequencing, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
Rawson T, moore L, Hernandez B, et al., 2017, A systematic review of clinical decision support systems for antimicrobial management: Are we failing to investigate these interventions appropriately?, Clinical Microbiology and Infection, Vol: 23, Pages: 524-532, ISSN: 1469-0691
ObjectivesClinical decision support systems (CDSS) for antimicrobial management can support clinicians to optimise antimicrobial therapy. We reviewed all original literature (qualitative and quantitative) to understand the current scope of CDSS for antimicrobial management and analyse existing methods used to evaluate and report such systems. MethodPRISMA guidelines were followed. Medline, EMBASE, HMIC Health and Management, and Global Health databases were searched from 1st January 1980 to 31st October 2015. All primary research studies describing CDSS for antimicrobial management in adults in primary or secondary care were included. For qualitative studies, thematic synthesis was performed. Quality was assessed using Integrated quality Criteria for the Review Of Multiple Study designs (ICROMS) criteria. CDSS reporting was assessed against a reporting framework for behaviour change intervention implementation.ResultsFifty-eight original articles were included describing 38 independent CDSS. The majority of systems target antimicrobial prescribing (29/38;76%), are platforms integrated with electronic medical records (28/38;74%), and have rules based infrastructure providing decision support (29/38;76%). On evaluation against the intervention reporting framework, CDSS studies fail to report consideration of the non-expert, end-user workflow. They have narrow focus, such as antimicrobial selection, and use proxy outcome measures. Engagement with CDSS by clinicians was poor.ConclusionGreater consideration of the factors that drive non-expert decision making must be considered when designing CDSS interventions. Future work must aim to expand CDSS beyond simply selecting appropriate antimicrobials with clear and systematic reporting frameworks for CDSS interventions developed to address current gaps identified in the reporting of evidence.
Hernandez B, Herrero P, Rawson TM, et al., 2017, Data-drivenWeb-based Intelligent Decision Support System for Infection Management at Point-Of-Care: Case-Based Reasoning Benefits and Limitations, 10th International Joint Conference on Biomedical Engineering Systems and Technologies, Publisher: SCITEPRESS, Pages: 119-127
Pesl P, Herrero P, Reddy M, et al., 2017, Case-Based Reasoning for Insulin Bolus Advice., J Diabetes Sci Technol, Vol: 11, Pages: 37-42
BACKGROUND: Insulin bolus calculators assist people with Type 1 diabetes (T1D) to calculate the amount of insulin required for meals to achieve optimal glucose levels but lack adaptability and personalization. We have proposed enhancing bolus calculators by the means of case-based reasoning (CBR), an established problem-solving methodology, by individualizing and optimizing insulin therapy for various meal situations. CBR learns from experiences of past similar meals, which are described in cases through a set of parameters (eg, time of meal, alcohol, exercise). This work discusses the selection, representation and effect of case parameters used for a CBR-based Advanced Bolus Calculator for Diabetes (ABC4D). METHODS: We analyzed the usage and effect of selected parameters during a pilot study (n = 10), where participants used ABC4D for 6 weeks. Retrospectively, we evaluated the effect of glucose rate of change before the meal on the glycemic excursion. Feedback from study participants about the choice of parameters was obtained through a nonvalidated questionnaire. RESULTS: Exercise and alcohol were the most frequently used parameters, which was congruent with the feedback from study participants, who found these parameters most useful. Furthermore, cases including either exercise or alcohol as parameter showed a trend in reduction of insulin at the end of the study. A significant difference ( P < .01) was found in glycemic outcomes for meals where glucose rate of change was rising compared to stable rate of change. CONCLUSIONS: Results from the 6-week study indicate the potential benefit of including parameters exercise, alcohol and glucose-rate of change for insulin dosing decision support.
Snoeijs J, Georgiou P, Carrara S, 2017, CMOS Body Dust - Towards Drinkable Diagnostics, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, ISSN: 2163-4025
Douthwaite M, Georgiou P, 2017, Temperature Compensation for ISFETs using a Floating Gate Current Mirror, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, ISSN: 2163-4025
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Douthwaite M, Georgiou P, 2017, Live Demonstration: A Batteryless CMOS ISFET Array Powered by Body Heat for Real-Time Monitoring of Bio-fluids, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, ISSN: 2163-4025
Rawson T, Charani E, Moore L, et al., 2016, Vancomycin therapy in secondary care; investigating factors that impact therapeutic target attainment, Journal of Infection, Vol: 74, Pages: 320-324, ISSN: 1532-2742
Rawson T, Charani E, Moore L, et al., 2016, Mapping the decision pathways of acute infection management in secondary care among UK medical physicians: a qualitative study, BMC Medicine, Vol: 14, ISSN: 1741-7015
BackgroundThe inappropriate use of antimicrobials drives antimicrobial resistance. We conducted a study to map physician decision making processes for acute infection management in secondary care to identify potential targets for quality improvement interventions.MethodsNewly qualified to Consultant level physicians participated in semi-structured interviews. Interviews were audio recorded and transcribed verbatim for analysis using NVIVO11.0 software. Grounded theory methodology was applied. Analytical categories were created using constant comparison approach to the data and participants were recruited to the study until thematic saturation was reached. ResultsTwenty physicians were interviewed. The decision pathway for the management of acute infections follows a Bayesian-like step-wise approach, with information processed and systematically added to prior assumptions to guide management. The main emerging themes identified as determinants of the decision making of individual physicians were; (i) perceptions of providing “optimal” care for the patient with infection by providing rapid and often intravenous therapy; (ii) perceptions that stopping/de-escalating therapy was a senior doctor decision with junior trainees not expected to contribute; (iii) expectation of interactions with local guidelines and microbiology service advice. Feedback on review of junior doctor prescribing decisions was often lacking, causing frustration and confusion on appropriate practice within this cohort. ConclusionInterventions to improve infection management must incorporate mechanisms to promote distribution of responsibility for decisions made. The disparity between expectations of prescribers to start but not review/stop therapy requires addressing urgently with mechanisms to improve communication and feedback to junior prescribers to facilitate their continued development as prudent antimicrobial prescribers.
Rawson T, Moore L, Hernandez B, et al., 2016, Patient engagement with infection management in secondary care: a qualitative investigation of current experiences, BMJ Open, Vol: 6, ISSN: 2044-6055
Objective To understand patient engagement with decision-making for infection management in secondary care and the consequences associated with current practices.Design A qualitative investigation using in-depth focus groups.Participants Fourteen members of the public who had received antimicrobials from secondary care in the preceding 12 months in the UK were identified for recruitment. Ten agreed to participate. All participants had experience of infection management in secondary care pathways across a variety of South-East England healthcare institutes. Study findings were subsequently tested through follow-up focus groups with 20 newly recruited citizens.Results Participants reported feelings of disempowerment during episodes of infection in secondary care. Information is communicated in a unilateral manner with individuals ‘told’ that they have an infection and will receive an antimicrobial (often unnamed), leading to loss of ownership, frustration, anxiety and ultimately distancing them from engaging with decision-making. This poor communication drives individuals to seek information from alternative sources, including online, which is associated with concerns over reliability and individualisation. Failures in communication and information provision by clinicians in secondary care influence individuals’ future ideas about infections and their management. This alters their future actions towards antimicrobials and can drive prescription non-adherence and loss to follow-up.Conclusions Current infection management and antimicrobial prescribing practices in secondary care fail to engage patients with the decision-making process. Secondary care physicians must not view infection management episodes as discrete events, but as cumulative experiences which have the potential to shape future patient behaviour and understanding of antimicrobial use.
Moser N, Lande TS, Toumazou C, et al., 2016, ISFETs in CMOS and Emergent Trends in Instrumentation: A Review, IEEE Sensors Journal, Vol: 16, Pages: 6496-6514, ISSN: 1530-437X
Over the past decade, ion-sensitive field-effect transistors (ISFETs) have played a major role in enabling the fabrication of fully integrated CMOS-based chemical sensing systems. This has allowed several new application areas, with the most promising being the fields of ion imaging and full genome sequencing. This paper reviews the new trends in front-end topologies toward the design of ISFET sensing arrays in CMOS for these new applications. More than a decade after the review of the ISFET by Bergveld which summarized the state of the art in terms of device and early readout circuity, we describe the evolution in terms of device macromodel and identify the main sensor challenges for current designers. We analyze the techniques that have been reported for both ISFET instrumentation and compensation, and conclude that topologies are focusing on device adaptation for offset and drift cancellation, as opposed to system compensation which are often not as robust. Guidelines are provided to build a tailored CMOS ISFET array, emphasizing that the needs in terms of applications are the keys to selecting the right pixel architecture. Over the next few years, the race for the largest and densest array is likely to be put on hold to allow the research to focus on new pixel topologies, ultimately leading to the development of reliable and scalable arrays. A wide range of new applications are expected to motivate this paper for at least another decade.
Hu Y, Georgiou P, 2016, An Automatic Gain Control System for ISFET Array Compensation, IEEE Transactions on Circuits and Systems I: Regular Papers, Vol: 63, Pages: 1511-1520, ISSN: 1549-8328
This paper presents an automatic gain calibration system for ion-sensitive field effect transistors (ISFETs) sensing arrays which compensates for mismatch in the gain of the pixels. The system utilizes the high frequency spectrum of the sensed signal to superimpose a reference sine wave through the reference electrode, which allows identification and calibration of the local gain. The complete system has been fabricated in a 0.35 μm CMOS process and has been designed to achieve very high accuracy and a small settling time to allow fast pixel switching. Measured results confirm good performance with only a 1.15% deviation in gain caused by noise and harmonic distortion and a rapid settling time of 70.5 μs which is suitable for CMOS-based ISFET arrays.
Ghoreishizadeh S, Georgiou P, Carrara S, et al., 2016, An Integrated Platform for Differential Electrochemical and ISFET Sensing, IEEE ISCAS 2016, Publisher: IEEE, Pages: 2875-2878, ISSN: 2379-447X
A fully-integrated differential biosensing platform on CMOS is presented for miniaturized enzyme-based electrochemical sensing. It enables sensor background current elimination and consists of a differential sensor array and a differential readout IC (DiRIC). The sensor array includes a four-electrode sensor for amperometric electrochemical sensing, as well as a differential ISFET-based pH sensor to calibrate the biosensors. The ISFET is biased in weak inversion and co-designed with DiRIC to enable pH measurements from 1 to 14 with resolution of 0.1 pH. DiRIC enables differential current measurement in the range of ¿¿100 ¿¿A with more than 120dB dynamic range.
Reddy M, Pesl P, Xenou M, et al., 2016, Clinical Safety and Feasibility of the Advanced Bolus Calculator for Type 1 Diabetes Based on Case-Based Reasoning: A 6-Week Nonrandomized Single-Arm Pilot Study., Diabetes Technol Ther, Vol: 18, Pages: 487-493
BACKGROUND: The Advanced Bolus Calculator for Diabetes (ABC4D) is an insulin bolus dose decision support system based on case-based reasoning (CBR). The system is implemented in a smartphone application to provide personalized and adaptive insulin bolus advice for people with type 1 diabetes. We aimed to assess proof of concept, safety, and feasibility of ABC4D in a free-living environment over 6 weeks. METHODS: Prospective nonrandomized single-arm pilot study. Participants used the ABC4D smartphone application for 6 weeks in their home environment, attending the clinical research facility weekly for data upload, revision, and adaptation of the CBR case base. The primary outcome was postprandial hypoglycemia. RESULTS: Ten adults with type 1 diabetes, on multiple daily injections of insulin, mean (standard deviation) age 47 (17), diabetes duration 25 (16), and HbA1c 68 (16) mmol/mol (8.4 (1.5) %) participated. A total of 182 and 150 meals, in week 1 and week 6, respectively, were included in the analysis of postprandial outcomes. The median (interquartile range) number of postprandial hypoglycemia episodes within 6-h after the meal was 4.5 (2.0-8.2) in week 1 versus 2.0 (0.5-6.5) in week 6 (P = 0.1). No episodes of severe hypoglycemia occurred during the study. CONCLUSION: The ABC4D is safe for use as a decision support tool for insulin bolus dosing in self-management of type 1 diabetes. A trend suggesting a reduction in postprandial hypoglycemia was observed in the final week compared with week 1.
Koutsos E, Cretu V, Georgiou P, 2016, A muscle fibre conduction velocity tracking ASIC for local fatigue monitoring, IEEE Transactions on Biomedical Circuits and Systems, Vol: 10, Pages: 1119-1128, ISSN: 1940-9990
Electromyography analysis can provide information about a muscle's fatigue state by estimating Muscle Fibre Conduction Velocity (MFCV), a measure of the travelling speed of Motor Unit Action Potentials (MUAPs) in muscle tissue. MFCV better represents the physical manifestations of muscle fatigue, compared to the progressive compression of the myoelectic Power Spectral Density, hence it is more suitable for a muscle fatigue tracking system. This paper presents a novel algorithm for the estimation of MFCV using single threshold bit-stream conversion and a dedicated application-specified integrated circuit (ASIC) for its implementation, suitable for a compact, wearable and easy to use muscle fatigue monitor. The presented ASIC is implemented in a commercially available AMS 0.35 [Formula: see text] CMOS technology and utilizes a bit-stream cross-correlator that estimates the conduction velocity of the myoelectric signal in real time. A test group of 20 subjects was used to evaluate the performance of the developed ASIC, achieving good accuracy with an error of only 3.2% compared to Matlab.
Georgiou P, Pesl P, Oliver N, et al., 2016, An Advanced Insulin Bolus Calculator for Type 1 Diabetes, Wireless Medical Systems and Algorithms Design and Applications, Publisher: CRC Press, ISBN: 9781498700788
Design and Applications Pietro Salvo, Miguel Hernandez-Silveira ... VLSI: Circuits for Emerging Applications Tomasz Wojcicki Wireless Medical Systems and Algorithms: Design and Applications ... Wireless Technologies: Circuits, Systems, and Devices Krzysztof Iniewski Wireless Transceiver Circuits: System Perspectives ...
Hu Y, Georgiou P, 2016, A Real-Time <i>de novo</i> DNA Sequencing Assembly Platform Based on an FPGA Implementation, IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, Vol: 13, Pages: 291-300, ISSN: 1545-5963
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- Citations: 3
Herrero P, Bondia J, Amparo G, et al., 2016, A BIHORMONAL GLUCOSE CONTROLLER BASED ON THE PARACRINE INTERACTION BETWEEN BETA CELL AND ALPHA CELL, Publisher: MARY ANN LIEBERT, INC, Pages: A57-A58, ISSN: 1520-9156
Pesl P, Herrero P, Reddy M, et al., 2016, AUGMENTING AN ADVANCED BOLUS CALCULATOR WITH CONTINUOUS GLUCOSE MONITORING AND A SMARTWATCH, Publisher: MARY ANN LIEBERT, INC, Pages: A97-A97, ISSN: 1520-9156
El Sharkawy M, Herrero P, Reddy M, et al., 2016, A LOW-POWER BIO-INSPIRED ARTIFICIAL PANCREAS, Publisher: MARY ANN LIEBERT, INC, Pages: A54-A54, ISSN: 1520-9156
Ramkissoon CM, Herrero P, Bondia J, et al., 2016, AUTOMATIC DETECTION OF EXERCISE IN PEOPLE WITH TYPE 1 DIABETES USING AN UNSCENTED KALMAN FILTER, Publisher: MARY ANN LIEBERT, INC, Pages: A56-A56, ISSN: 1520-9156
Pesl P, Herrero P, Reddy M, et al., 2016, GLUCOSE RATE-OF-CHANGE AT MEAL TIMES FOR INSULIN DOSING DECISION SUPPORT, Publisher: MARY ANN LIEBERT, INC, Pages: A97-A97, ISSN: 1520-9156
Reddy M, Pesl P, Xenou M, et al., 2016, CLINICAL SAFETY AND FEASIBILITY OF THE ADVANCED BOLUS CALCULATOR FOR TYPE 1 DIABETES BASED ON CASE-BASED REASONING: A 6-WEEK NON-RANDOMISED SINGLE-ARM PILOT STUDY, DIABETES TECHNOLOGY & THERAPEUTICS, Vol: 18, Pages: A34-A35, ISSN: 1520-9156
Herrero P, Delaunay B, Jaulin L, et al., 2016, Robust set-membership parameter estimation of the glucose minimal model, INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Vol: 30, Pages: 173-185, ISSN: 0890-6327
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- Citations: 4
Georgiou P, Johnston D, 2016, Biomedical and Health Informatics for Diabetes, IEEE Journal of Biomedical and Health Informatics, Vol: 20, Pages: 3-3, ISSN: 2168-2208
Moser N, Lande TS, Georgiou P, 2016, Scaling ISFET Instrumentation with In-Pixel Quantisation to Deep Submicron Technologies, 12th IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 436-439, ISSN: 2163-4025
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- Citations: 7
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