Publications
410 results found
Elmantawi K, Miscourides N, Koutsos E, et al., 2018, A 96-channel ASIC for sEMG Fatigue Monitoring with Compressed Sensing for Data Reduction, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
Zeng J, Miscourides N, Georgiou P, 2018, A 128×128 Current-Mode Ultra-High Frame Rate ISFET Array for Ion Imaging, ISSN: 0271-4310
This paper presents a 128 × 128 ISFET array with current mode readout peripherals for real-time ion imaging. Current-mode operation is employed to achieve very high speed and frame rate and provide a linear mapping between the ion concentration at the sensing layer (typically hydrogen ions - pH) to the drain current of the device. To this effect, a single device biased in the triode region can serve as both the sensing and readout device in the pixel ensuring a very small area footprint per pixel. Compensating for known non-ideal effects of the ISFET, namely trapped charge and drift, is implemented by resetting the gate voltage whereas any additional circuit offsets are eliminated by auto-zeroing. Auto-zeroing and sampling takes place on a row-parallel basis which is then multiplexed to 8 current mode ADCs. The chip is designed in a standard 0.35um CMOS process, occupies an area of 2.6mm × 2.2mm and can achieve a frame rate of 3000 fps which is the highest in this process node. We anticipate that the proposed system will increase the current temporal limit of detection of chemical reactions and provide new insight into real-time ion dynamics.
Schires E, Georgiou P, Lande TS, 2018, Vital Sign Monitoring Through the Back Using an UWB Impulse Radar With Body Coupled Antennas, IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, Vol: 12, Pages: 292-302, ISSN: 1932-4545
Moser N, Rodriguez-Manzano J, Lande TS, et al., 2018, A scalable ISFET sensing and memory array with sensor auto-calibration for on-chip real-time DNA detection, IEEE Transactions on Biomedical Circuits and Systems, Vol: 12, Pages: 390-401, ISSN: 1932-4545
This paper presents a novel CMOS-based system-onchip with a 78 × 56 ion-sensitive field-effect transistor array using in-pixel quantization and compensation of sensor nonidealities. The pixel integrates sensing circuitry and memory cells to encode the ion concentration in time and store a calibration value per pixel. Temperature sensing pixels spread throughout the array allow temperature monitoring during the reaction. We describe the integration of the array as part of a lab-on-chip cartridge that plugs into a motherboard for power management, biasing, data acquisition, and temperature regulation. This forms a robust ion detection platform, which is demonstrated as a pH sensing system. We show that our calibration is able to perform readout with a linear spread of 0.3% and that the system exhibits a high pH sensitivity of 3.2 μs/pH. The complete system is shown to perform on-chip realtime DNA amplification and detection of lambda phage DNA by loop-mediated isothermal amplification.
Rawson T, o'hare D, Herrero P, et al., 2018, Delivering precision antimicrobial therapy through closed-loop control systems, Journal of Antimicrobial Chemotherapy, Vol: 73, Pages: 835-843, ISSN: 0305-7453
Sub-optimal exposure to antimicrobial therapy is associated with poor patient outcomes and the development of antimicrobial resistance. Mechanisms for optimizing the concentration of a drug within the individual patient are under development. However, several barriers remain in realizing true individualization of therapy. These include problems with plasma drug sampling, availability of appropriate assays, and current mechanisms for dose adjustment. Biosensor technology offers a means of providing real-time monitoring of antimicrobials in a minimally invasive fashion. We report the potential for using microneedle biosensor technology as part of closed-loop control systems for the optimization of antimicrobial therapy in individual patients.
Rawson T, Moore L, Castro Sanchez E, et al., 2018, Development of a patient-centred intervention to improve knowledge and understanding of antibiotic therapy in secondary care, Antimicrobial Resistance and Infection Control, Vol: 7, ISSN: 2047-2994
Introduction: We developed a personalised antimicrobial information module co-designed with patients. This study aimed to evaluate the potential impact of this patient-centred intervention on short-term knowledge and understanding of antimicrobial therapy in secondary care. Methods:Thirty previous patients who had received antibiotics in hospital within 12 months were recruited to co-design an intervention to promote patient engagement with infection management. Two workshops, containing five focus-groups were held. These were audio-recorded. Data were analysed using a thematic framework developed deductively based on previous work. Line-by-line coding was performed with new themes added to the framework by two researchers. This was used to inform the development of a patient information module, embedded within an electronic decision support tool (CDSS). The intervention was piloted over a four-week period at Imperial College Healthcare NHS Trust on 30 in-patients. Pre- and post-intervention questionnaires were developed and implemented to assess short term changes in patient knowledge and understanding and provide feedback on the intervention. Data were analysed using SPSS and NVIVO software. Results: Within the workshops, there was consistency in identified themes. The participants agreed upon and co-designed a personalised PDF document that could be integrated into an electronic CDSS to be used by healthcare professionals at the point-of-care. Their aim for the tool was to provide individualised practical information, signpost to reputable information sources, and enhance communication between patients and healthcare professionals.Eighteen out of thirty in-patients consented to participant in the pilot evaluation with 15/18(83%) completing the study. Median (range) age was 66(22-85) years. The majority were male (10/15;66%). Pre-intervention, patients reported desiring further information regarding their infections and antibiotic therapy, including side effects
Herrero P, Bondia J, Giménez M, et al., 2018, Automatic adaptation of Basal insulin using sensor-augmented pump therapy, Journal of Diabetes Science and Technology, Vol: 12, Pages: 282-294, ISSN: 1932-2968
BACKGROUND: People with insulin-dependent diabetes rely on an intensified insulin regimen. Despite several guidelines, they are usually impractical and fall short in achieving optimal glycemic outcomes. In this work, a novel technique for automatic adaptation of the basal insulin profile of people with diabetes on sensor-augmented pump therapy is presented. METHODS: The presented technique is based on a run-to-run control law that overcomes some of the limitations of previously proposed methods. To prove its validity, an in silico validation was performed. Finally, the artificial intelligence technique of case-based reasoning is proposed as a potential solution to deal with variability in basal insulin requirements. RESULTS: Over a period of 4 months, the proposed run-to-run control law successfully adapts the basal insulin profile of a virtual population (10 adults, 10 adolescents, and 10 children). In particular, average percentage time in target [70, 180] mg/dl was significantly improved over the evaluated period (first week versus last week): 70.9 ± 11.8 versus 91.1 ± 4.4 (adults), 46.5 ± 11.9 versus 80.1 ± 10.9 (adolescents), 49.4 ± 12.9 versus 73.7 ± 4.1 (children). Average percentage time in hypoglycemia (<70 mg/dl) was also significantly reduced: 9.7 ± 6.6 versus 0.9 ± 1.2 (adults), 10.5 ± 8.3 versus 0.83 ± 1.0 (adolescents), 10.9 ± 6.1 versus 3.2 ± 3.5 (children). When compared against an existing technique over the whole evaluated period, the presented approach achieved superior results on percentage of time in hypoglycemia: 3.9 ± 2.6 versus 2.6 ± 2.2 (adults), 2.9 ± 1.9 versus 2.0 ± 1.5 (adolescents), 4.6 ± 2.8 versus 3.5 ± 2.0 (children), without increasing the percentage time in hyperglycemia. CONCLUSION: The present study shows the potential of a novel technique to effectively adjust the basal insulin profile of a type 1 diab
Ghoreishizadeh S, Zhang X, Sharma S, et al., 2018, Study of electrochemical impedance of a continuous glucose monitoring sensor and its correlation with sensor performance, IEEE Sensors Letters, Vol: 2, ISSN: 2475-1472
Abstract:In this work, we study the change in the sensitivity and the electrochemical impedance of continuous glucose monitoring sensors over time. 28-day sensitivity and EIS measurement results on four similar sensors are presented. The sensitivity of the sensor is observed to be related to its double-layer capacitance and charge-transfer resistance, based on results acquired from a sensor that showed substantial sensitivity drop. Two data clusters are extracted that relate the sensor sensitivity to its impedance before and after the sensitivity drops by more than 50%.
Chiou S, Koutsos E, Georgiou P, et al., 2018, Association between spectral characteristics of paraspinal muscles and functional disability in low back pain patients: a cohort study, BMJ Open, Vol: 8, ISSN: 2044-6055
Objectives. Characteristics of muscle activity, represented by surface electromyography (EMG), have revealed differences between patients with low back pain and healthy adults; how they relate to functional and clinical parameters remains unclear. The purpose of the current study was to examine the correlation between frequency characteristics of EMG (analysed using continuous wavelet transform (CWT) analysis) and patients’ self-rated score of disability. Design and setting. This is a case control study with fifteen patients with mechanical low back pain (LBP) without radicular symptoms. Patients were recruited from the orthopaedic clinic at Charing Cross Hospital. Ten healthy adults were recruited from the staff working in the hospital and associated university. Patients completed the Roland-Morris Disability Questionnaire (RMDQ) and bilateral EMG activity was obtained from erector spinae at vertebral levels L4 and T12. Subjects performed 3 brief maximal isometric voluntary contractions (MVCs) of the back extensors and the torque was measured using a dynamometer. CWT was applied to the EMG signals of each muscle in a 200ms window centred around the peak torque obtained during the MVCs. The ratio (low/high frequencies) of the energy, the peak power, and the frequency of the peak power were calculated for each recording site, averaged and correlated with the individual’s RMDQ score. Results. Patients had lower peak power (T12 and L4) and lower frequency of the peak power (at T12) than the healthy adults. Additionally, RMDQ positively correlated to the average ratio of energy at T12 (rho=0.63; p=0.012), i.e. greater self-rated disability corresponded to a dominant distribution of energy in the lower frequencies. Conclusion. The current findings reveal alterations in EMG profile and its association with self-related back pain disability, suggesting that spectral characteristics of EMG reflect muscle function.
Li K, Liu F, Dong H, et al., 2018, A DEEP LEARNING PLATFORM FOR DIABETES BIG DATA ANALYSIS, Publisher: MARY ANN LIEBERT, INC, Pages: A116-A116, ISSN: 1520-9156
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- Citations: 2
Liu C, Oliver N, Georgiou P, et al., 2018, GLUCOSE FORECASTING USING A PHYSIOLOGICAL MODEL AND STATE ESTIMATION, Publisher: MARY ANN LIEBERT, INC, Pages: A76-A77, ISSN: 1520-9156
Pau H, Yong CM, Jordan L, et al., 2018, TYPE 1 DIABETES EXPERIENCE SIMULATOR APP, Publisher: MARY ANN LIEBERT, INC, Pages: A119-A119, ISSN: 1520-9156
Tanzanakis A, Herrero P, Georgiou P, 2018, A NOVEL ADAPTIVE ARTIFICIAL PANCREAS USING REINFORCEMENT LEARNING AND ITERATIVE LEARNING CONTROL: AN IN SILICO VALIDATION, Publisher: MARY ANN LIEBERT, INC, Pages: A61-A61, ISSN: 1520-9156
Yu LS, Moser N, Au A, et al., 2018, A CMOS based lab-on-chip diagnostic system for rapid detection and serotyping of the dengue virus, Pages: 298-300
Dengue virus outbreaks pose an ongoing threat to public health. Here, we report an innovative point-of-care diagnostic device, capable of simultaneous dengue detection, serotyping and real-time reporting. Our platform comprised an ISFET-based system, with 78x56 ISFET array permitting DNA/RNA amplification and detection, as well as an Android OS application on a smart phone to collect and report infections. Both synthetic and clinical sample validations confirm a change of pH when tested for the presence of dengue viral RNAs. These results show that our platform has the potential to accelerate the screening of 4 dengue serotype infections in order to provide rapid diagnostics and the real-time surveillance.
Malpartida-Cardenas K, Miscourides N, Yu LS, et al., 2018, A CMOS-based diagnostic system for detection of artemisinin-resistant malaria, Pages: 871-873
Rapid, sensitive and specific detection of single nucleotide polymorphisms (SNPs) at the point-of-care is urgently needed, specially related to the emergence of drug-resistant malaria. Here, we report a novel biosensing platform combining complementary metal-oxide semiconductor technology and loop-mediated isothermal amplification for the detection of SNPs related to artemisinin-resistant malaria. The proposed biosensing platform has shown rapid and specific detection of drug-resistant SNPs in less than 20 min, which is ideal for point-of-care diagnosis and treatment guidance.
Douthwaite M, Georgiou P, 2018, An Asynchronous Auto-biasing Circuit for Wearable Electrochemical Sensors., Publisher: IEEE, Pages: 1-4
Hu Y, Georgiou P, 2018, Trapped charge cancellation for CMOS ISFET sensors via Direct Tunnelling., Publisher: IEEE, Pages: 1-4
Douthwaite M, Georgiou P, 2017, Live Demonstration: An NFC based Batteryless CMOS ISFET Array for Real-Time pH Measurements of Bio-fluids, 16th IEEE SENSORS CONFERENCE, Publisher: IEEE, Pages: 469-469, ISSN: 1930-0395
Douthwaite M, Georgiou P, 2017, Live demonstration: An NFC based batteryless CMOS ISFET array for real-time pH measurements of bio-fluids, ISSN: 1930-0395
We demonstrate a low-power CMOS ISFET array for pH sensing which is inductively powered using NFC. Each pixel in a 3-by-3 array contains an ISFET operating in weak-inversion which detects changes in pH as a current. The output of all pixels is then averaged and converted to a frequency using a current-starved ring oscillator. We make use of a commercial NFC IC, the SIC4310, to harvest power from a standard smartphone and power the ASIC, which consumes up to 6 pW. The output frequency of the ASIC is then transferred to the phone to provide a real-time measurement of pH from a batteryless platform.
Hernandez Perez B, Herrero Viñas P, Miles Rawson T, et al., 2017, Supervised Learning for Infection Risk Inference Using Pathology Data, BMC Medical Informatics and Decision Making, Vol: 17, ISSN: 1472-6947
Background: Antimicrobial Resistance is threatening our ability to treat common infectious diseases and overuse of antimicrobials to treat human infections in hospitals is accelerating this process. Clinical Decision Support Systems (CDSSs) have been proven to enhance quality of care by promoting change in prescription practices through antimicrobial selection advice. However, bypassing an initial assessment to determine the existence of an underlying disease that justifies the need of antimicrobial therapy might lead to indiscriminate and often unnecessary prescriptions.Methods: From pathology laboratory tests, six biochemical markers were selected and combined with microbiology outcomes from susceptibility tests to create a unique dataset with over one and a half million daily profiles to perform infection risk inference. Outliers were discarded using the inter-quartile range rule and several sampling techniques were studied to tackle the class imbalance problem. The first phase selects the most effective and robust model during training using four-fold stratified cross-validation. The second phase evaluates the final model after isotonic calibration in scenarios with missing inputs and imbalanced class distributions. Results: More than 50\% of infected profiles have daily requested laboratory tests for the six biochemical markers with very promising infection inference results: area under the receiver operating characteristic curve (0.80-0.83), sensitivity (0.64-0.75) and specificity (0.92-0.97). Standardization consistently outperforms normalization and sensitivity is enhanced by using the SMOTE sampling technique. Furthermore, models operated without noticeable loss in performance if at least four biomarkers were available.Conclusion: The selected biomarkers comprise enough information to perform infection risk inference with a high degree of confidence even in the presence of incomplete and imbalanced data. Since they are commonly available in hospitals, Clini
Douthwaite M, Koutsos E, Yates DC, et al., 2017, A thermally powered ISFET array for on-body pH measurement, IEEE Transactions on Biomedical Circuits and Systems, Vol: 11, Pages: 1324-1334, ISSN: 1932-4545
Recent advances in electronics and electrochemical sensors have led to an emerging class of next generation wearables, detecting analytes in biofluids such as perspiration. Most of these devices utilize ion-selective electrodes (ISEs) as a detection method; however, ion-sensitive field-effect transistors (ISFETs) offer a solution with improved integration and a low power consumption. This work presents a wearable, thermoelectrically powered system composed of an application-specific integrated circuit (ASIC), two commercial power management integrated circuits and a network of commercial thermoelectric generators (TEGs). The ASIC is fabricated in 0.35 μm CMOS and contains an ISFET array designed to read pH as a current, a processing module which averages the signal to reduce noise and encodes it into a frequency, and a transmitter. The output frequency has a measured sensitivity of 6 to 8 kHz/pH for a pH range of 7-5. It is shown that the sensing array and processing module has a power consumption 6 μW and, therefore, can be entirely powered by body heat using a TEG. Array averaging is shown to reduce noise at these low power levels to 104 μV (input referred integrated noise), reducing the minimum detectable limit of the ASIC to 0.008 pH units. The work forms the foundation and proves the feasibility of battery-less, on-body electrochemical for perspiration analysis in sports science and healthcare applications.
Douthwaite M, Koutsos E, Yates DC, et al., 2017, A Thermally Powered ISFET Array for On-Body pH Measurement., IEEE Trans. Biomed. Circuits and Systems, Vol: 11, Pages: 1324-1334
Georgiou P, Koutsos E, 2017, Microelectronics for Muscle Fatigue Monitoring Through Surface EMG., CMOS Circuits for Biological Sensing and Processing, Publisher: Springer, ISBN: 9783319677231
This book provides the most comprehensive and consistent survey of the field of IC design for Biological Sensing and Processing.
Stewart CE, Moseley MJ, Georgiou P, et al., 2017, Occlusion dose monitoring in amblyopia therapy: status, insights, and future directions, JOURNAL OF AAPOS, Vol: 21, Pages: 402-406, ISSN: 1091-8531
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- Citations: 15
Moser N, Rodriguez-Manzano J, Yu L-S, et al., 2017, Live Demonstration: A CMOS-Based ISFET Array for Rapid Diagnosis of the Zika Virus, IEEE International Symposium on Circuits and Systems (ISCAS) 2017, ISSN: 2379-447X
We demonstrate a diagnostics platform which integrates an ISFET array and a temperature control loop for isothermal DNA detection. The controller maintains a temperature of 63◦C to perform nucleic acid amplification which is detected by the on-chip sensors. The 32x32 ISFET array is first calibrated to cancel trapped charge and then measures the change in the pH of the reaction. The sensor data is sent to a microcontroller and the reaction is monitored in real-time using a MATLAB interface. Experiments confirm a change of 0.9 pH when tested for the presence of RNA associated with the Zika virus.
Herrero P, Bondia J, Oliver N, et al., 2017, A coordinated control strategy for insulin and glucagon delivery in type 1 diabetes, Computer Methods in Biomechanics and Biomedical Engineering, Vol: 20, Pages: 1474-1482, ISSN: 1025-5842
Type 1 diabetes is an autoimmune condition characterised by a pancreatic insulin secretion deficit, resulting in high blood glucose concentrations, which can lead to micro- and macrovascular complications. Type 1 diabetes also leads to impaired glucagon production by the pancreatic α-cells, which acts as a counter-regulatory hormone to insulin. A closed-loop system for automatic insulin and glucagon delivery, also referred to as an artificial pancreas, has the potential to reduce the self-management burden of type 1 diabetes and reduce the risk of hypo- and hyperglycemia. To date, bihormonal closed-loop systems for glucagon and insulin delivery have been based on two independent controllers. However, in physiology, the secretion of insulin and glucagon in the body is closely interconnected by paracrine and endocrine associations. In this work, we present a novel biologically-inspired glucose control strategy that accounts for such coordination. An in silico study using an FDA-accepted type 1 simulator was performed to evaluate the proposed coordinated control strategy compared to its non-coordinated counterpart, as well as an insulin-only version of the controller. The proposed coordinated strategy achieves a reduction of hyperglycemia without increasing hypoglycemia, when compared to its non-coordinated counterpart.
Ghoreishizadeh S, Taurino I, De Micheli G, et al., 2017, A Differential Electrochemical Readout ASIC with Heterogeneous Integration of Bio-nano Sensors for Amperometric Sensing, IEEE Transactions on Biomedical Circuits and Systems, Vol: 11, Pages: 1148-1159, ISSN: 1940-9990
A monolithic biosensing platform is presented for miniaturized amperometric electrochemical sensing in CMOS. The system consists of a fully integrated current readout circuit for differential current measurement as well as on-die sensors developed by growing platinum nanostructures (Pt-nanoS) on top of electrodes implemented with the top metal layer. The circuit is based on the switch–capacitor technique and includes pseudodifferential integrators for concurrent sampling of the differential sensor currents. The circuit further includes a differential to single converter and a programmable gain amplifier prior to an ADC. The system is fabricated in 0.35 μm technology and measures current within ±20 μA with minimum input-referred noise of 0.47 pA and consumes 9.3 mW from a 3.3 V supply. Differential sensing for nanostructured sensors is proposed to build highly sensitive and offset-free sensors for metabolite detection. This is successfully tested for bio-nano-sensors for the measurement of glucose in submilli molar concentrations with the proposed readout IC. The on-die electrodes are nanostructured and cyclic voltammetry run successfully through the readout IC to demonstrate detection of H2O2.
Rawson TM, Sharma S, Georgiou P, et al., 2017, Towards a minimally invasive device for beta-lactam monitoring in humans, Electrochemistry Communications, Vol: 82, Pages: 1-5, ISSN: 1388-2481
Antimicrobial resistance is a leading patient safety issue. There is a need to develop novel mechanisms for monitoring and subsequently improving the precision of how we use antibiotics. A surface modified microneedle array was developed for monitoring beta-lactam antibiotic levels in human interstitial fluid. The sensor was fabricated by anodically electrodepositing iridium oxide (AEIROF) onto a platinum surface on the microneedle followed by fixation of beta-lactamase enzyme within a hydrogel. Calibration of the sensor was performed to penicillin-G in buffer solution (PBS) and artificial interstitial fluid (ISF). Further calibration of a platinum disc electrode was undertaken using amoxicillin and ceftriaxone. Open-circuit potentials were performed and data analysed using the Hill equation and log(concentration [M]) plots. The microneedle sensor demonstrated high reproducibility between penicillin-G runs in PBS with mean Km (± 1SD) = 0.0044 ± 0.0013 M and mean slope function of log(concentration plots) 29 ± 1.80 mV/decade (r2 = 0.933). Response was reproducible after 28 days storage at 4 °C. In artificial ISF, the sensors response was Km (± 1SD) = 0.0077 ± 0.0187 M and a slope function of 34 ± 1.85 mv/decade (r2 = 0.995). Our results suggest that microneedle array based beta-lactam sensing may be a future application of this AEIROF based enzymatic sensor.
Moser N, Panteli C, Ma D, et al., 2017, Improving the pH Sensitivity of ISFET Arrays withReactive Ion Etching, BioCAS 2017, Publisher: IEEE
In this paper, we report a method to improvesensitivity for CMOS ISFET arrays using Reactive Ion Etching(RIE) as a post-processing technique. The process etches awaythe passivation layers of the commercial CMOS process, using anoxygen (O2) and sulfur hexafluoride (SF6) plasma. The resultingattenuation and pH sensitivity are characterised for five diesetched for 0 to 15 minutes, and we demonstrate that capacitiveattenuation is reduced by 196% and pH sensitivity increasedby 260% compared to the non-etched equivalent. The spread oftrapped charge is also reduced which relaxes requirements on theanalogue front-end. The technique significantly improves the performanceof the fully-integrated sensing system for applicationssuch as DNA detection.
Herrero P, Bondia J, Adewuyi O, et al., 2017, Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra- day variability, Computer Methods and Programs in Biomedicine, Vol: 146, Pages: 125-131, ISSN: 0169-2607
Background and ObjectiveCurrent prototypes of closed-loop systems for glucose control in type 1 diabetes mellitus, also referred to as artificial pancreas systems, require a pre-meal insulin bolus to compensate for delays in subcutaneous insulin absorption in order to avoid initial post-prandial hyperglycemia. Computing such a meal bolus is a challenging task due to the high intra-subject variability of insulin requirements. Most closed-loop systems compute this pre-meal insulin dose by a standard bolus calculation, as is commonly found in insulin pumps. However, the performance of these calculators is limited due to a lack of adaptiveness in front of dynamic changes in insulin requirements. Despite some initial attempts to include adaptation within these calculators, challenges remain.MethodsIn this paper we present a new technique to automatically adapt the meal-priming bolus within an artificial pancreas. The technique consists of using a novel adaptive bolus calculator based on Case-Based Reasoning and Run-To-Run control, within a closed-loop controller. Coordination between the adaptive bolus calculator and the controller was required to achieve the desired performance. For testing purposes, the clinically validated Imperial College Artificial Pancreas controller was employed. The proposed system was evaluated against itself but without bolus adaptation. The UVa-Padova T1DM v3.2 system was used to carry out a three-month in silico study on 11 adult and 11 adolescent virtual subjects taking into account inter-and intra-subject variability of insulin requirements and uncertainty on carbohydrate intake.ResultsOverall, the closed-loop controller enhanced by an adaptive bolus calculator improves glycemic control when compared to its non-adaptive counterpart. In particular, the following statistically significant improvements were found (non-adaptive vs. adaptive). Adults: mean glucose 142.2 ± 9.4 vs. 131.8 ± 4.2 mg/dl; perce
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