Publications
410 results found
Haci D, Liu Y, Nikolic K, et al., 2018, Thermally controlled lab-on-PCB for biomedical applications, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 655-658
This paper reports on the implementation andcharacterisation of a thermally controlled device forin vitrobiomedical applications, based on standard Printed Circuit Board(PCB) technology. This is proposed as a low cost alternativeto state-of-the-art microfluidic devices and Lab-on-Chip (LoC)platforms, which we refer to as the thermal Lab-on-PCB concept.In total, six different prototype boards have been manufacturedto implement as many mini-hotplate arrays. 3D multiphysicssoftware simulations show the thermal response of the modelledmini-hotplate boards to electrical current stimulation, highlight-ing their versatile heating capability. A comparison with theresults obtained by the characterisation of the fabricated PCBsdemonstrates the dual temperature sensing/heating property ofthe mini-hotplate, exploitable in a larger range of temperaturewith respect to the typical operating range of LoC devices. Thethermal system is controllable by means of external off-the-shelfcircuitry designed and implemented on a single-channel controlboard prototype.
Cacho-Soblechero M, Lande TS, Georgiou P, 2018, A fully-digital ISFET front-end with In-Pixel ΣΔ Modulation
This paper presents a fully-digital pixel architecture for ISFET-based sensing. The sensed pH is transformed to the frequency domain through a Chemically Controlled Oscillator (CCO), generating a digital clock which is then modulated onto a noise-shaped PWM signal through a 1-blt Frequency-to-Digital ΣΔ Modulator (FDSM). The proposed architecture achieves a sensitivity of 536 Hz/pH at center frequency of 2.48 MHz. Implemented using 0.35μm CMOS technology, the pixel architecture occupies 75 μm × 75 μm with a power consumption of 66μW. This pixel can be fully scaled to deeper sub-micron technologies, potentially reaping benefits in terms of speed, area and power consumption.
Liu C, Vehi J, Oliver N, et al., 2018, Enhancing Blood Glucose Prediction with Meal Absorption and Physical Exercise Information
Objective: Numerous glucose prediction algorithm have been proposed toempower type 1 diabetes (T1D) management. Most of these algorithms only accountfor input such as glucose, insulin and carbohydrate, which limits theirperformance. Here, we present a novel glucose prediction algorithm which, inaddition to standard inputs, accounts for meal absorption and physical exerciseinformation to enhance prediction accuracy. Methods: a compartmental model ofglucose-insulin dynamics combined with a deconvolution technique for stateestimation is employed for glucose prediction. In silico data correspondingfrom the 10 adult subjects of UVa-Padova simulator, and clinical data from 10adults with T1D were used. Finally, a comparison against a validated glucoseprediction algorithm based on a latent variable with exogenous input (LVX)model is provided. Results: For a prediction horizon of 60 minutes, accountingfor meal absorption and physical exercise improved glucose forecastingaccuracy. In particular, root mean square error (mg/dL) went from 26.68 to23.89, p<0.001 (in silico data); and from 37.02 to 35.96, p<0.001 (clinicaldata - only meal information). Such improvement in accuracy was translated intosignificant improvements on hypoglycaemia and hyperglycaemia prediction.Finally, the performance of the proposed algorithm is statistically superior tothat of the LVX algorithm (26.68 vs. 32.80, p<0.001 (in silico data); 37.02 vs.49.17, p<0.01 (clinical data). Conclusion: Taking into account meal absorptionand physical exercise information improves glucose prediction accuracy.
Malpartida-Cardenas K, Rodriguez-Manzano J, Yu L-S, et al., 2018, Allele-specific isothermal amplification method using novel unmodified self-stabilizing competitive primers, Analytical Chemistry, Vol: 90, Pages: 11972-11980, ISSN: 0003-2700
Rapid and specific detection of single nucleotide polymorphisms (SNPs) related to drug resistance in infectious diseases is crucial for accurate prognostics, therapeutics and disease management at point-of-care. Here, we present a novel amplification method and provide universal guidelines for the detection of SNPs at isothermal conditions. This method, called USS-sbLAMP, consists of SNP-based loop-mediated isothermal amplification (sbLAMP) primers and unmodified self-stabilizing (USS) competitive primers that robustly delay or prevent unspecific amplification. Both sets of primers are incorporated into the same reaction mixture, but always targeting different alleles; one set specific to the wild type allele and the other to the mutant allele. The mechanism of action relies on thermodynamically favored hybridization of totally complementary primers, enabling allele-specific amplification. We successfully validate our method by detecting SNPs, C580Y and Y493H, in the Plasmodium falciparum kelch 13 gene that are responsible for resistance to artemisinin-based combination therapies currently used globally in the treatment of malaria. USS-sbLAMP primers can efficiently discriminate between SNPs with high sensitivity (limit of detection of 5 × 101 copies per reaction), efficiency, specificity and rapidness (<35 min) with the capability of quantitative measurements for point-of-care diagnosis, treatment guidance, and epidemiological reporting of drug-resistance.
Dahiya R, Georgiou P, Roberts R, et al., 2018, Selected Papers From the IEEE Sensors 2017 Conference, IEEE SENSORS JOURNAL, Vol: 18, Pages: 7764-7764, ISSN: 1530-437X
Herrero P, Rawson TM, Philip A, et al., 2018, Closed-loop control for precision antimicrobial delivery: an In silico proof-of-concept, IEEE Transactions on Biomedical Engineering, Vol: 65, Pages: 2231-2236, ISSN: 0018-9294
IEEE Objective: Inappropriate dosing of patients with antibiotics is a driver of antimicrobial resistance, toxicity, and poor outcomes of therapy. In this paper, we investigate, in silico, the hypothesis that the use of a closed-loop control system could improve the attainment of pharmacokinetic-pharmacodynamic targets for antimicrobial therapy, where wide variations in target attainment have been reported. This includes patients in critical care, patients with renal disease and patients with obesity.
Ma D, Rodriguez-Manzano J, Lopez SDM, et al., 2018, Adapting ISFETs for Epigenetics: An Overview, IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, Vol: 12, Pages: 1186-1201, ISSN: 1932-4545
Miscourides N, Yu L-S, Rodriguez-Manzano J, et al., 2018, A 12.8 k current-mode velocity-saturation ISFET array for on-chip real-time DNA detection, IEEE Transactions on Biomedical Circuits and Systems, Vol: 12, Pages: 1202-1214, ISSN: 1932-4545
This paper presents a large-scale CMOS chemical-sensing array operating in current mode for real-time ion imaging and detection of DNA amplification. We show that the current-mode operation of ion-sensitive field-effect transistors in velocity saturation devices can be exploited to achieve an almost perfect linearity in their input-output characteristics (pH-current), which are aligned with the continuous scaling trend of transistors in CMOS. The array is implemented in a 0.35-m process and includes 12.8 k sensors configured in a 2T per pixel topology. We characterize the array by taking into account nonideal effects observed with floating gate devices, such as increased pixel mismatch due to trapped charge and attenuation of the input signal due to the passivation capacitance, and show that the selected biasing regime allows for a sufficiently large linear range that ensures a linear pH to current despite the increased mismatch. The proposed system achieves a sensitivity of 1.03 A/pH with a pH resolution of 0.101 pH and is suitable for the real-time detection of the NDM carbapenemase gene in E. Coli using a loop-mediated isothermal amplification.
Herrero P, Rawson TM, Philip A, et al., 2018, Closed-Loop Control for Precision Antimicrobial Delivery: An In Silico Proof-of-Concept., IEEE Trans. Biomed. Engineering, Vol: 65, Pages: 2231-2236
Rodriguez-Manzano J, Moniri A, Malpartida-Cardenas K, et al., 2018, Simultaneous single-channel multiplex and quantification of carbapenem-resistant genes using multidimensional standard curves
<jats:title>ABSTRACT</jats:title><jats:p>Multiplexing and absolute quantification of nucleic acids, both have, in their own right, significant and extensive use in biomedical related fields, especially in point-of-care applications. Currently, the ability to detect several nucleic acid targets in a single-reaction scales linearly with the number of targets; an expensive and time-consuming feat. Here, we propose a new methodology based on multidimensional standard curves that extends the use of real-time PCR data obtained by common qPCR instruments. By applying this novel methodology, we achieve simultaneous single-channel multiplexing and enhanced quantification of multiple targets using only real-time amplification data. This is obtained without the need of fluorescent probes, agarose gels, melting curves or sequencing analysis. Given the importance and demand for tackling challenges in antimicrobial resistance, the proposed method is applied to the four most prominent carbapenem-resistant genes:<jats:italic>bla</jats:italic><jats:sub>OXA-48</jats:sub>,<jats:italic>bla</jats:italic><jats:sub>NDM</jats:sub>,<jats:italic>bla</jats:italic><jats:sub>VIM</jats:sub>and<jats:italic>bla</jats:italic><jats:sub>KPC</jats:sub>, which account for 97% of the UK’s reported carbapenemase-producing Enterobacteriaceae.</jats:p>
Nagulapalli R, Hayatleh K, Barker S, et al., 2018, A 0.55 v Bandgap Reference with a 59 ppm/ ° C Temperature Coefficient, Journal of Circuits, Systems and Computers, ISSN: 0218-1266
© 2019 World Scientific Publishing Company. This paper presents a novel low power, low voltage CMOS bandgap reference (BGR) that overcomes the problems with the existing BJT-based reference circuits by using a MOS transistor operating in sub-threshold region. A proportional to absolute temperature (PTAT) voltage is generated by exploiting the self-bias cascode branch, while a Complementary to Absolute Temperature (CTAT) voltage is generated by using the threshold voltage of the transistor. The proposed circuit is implemented in 65nm CMOS technology. Post-layout simulation results show that the proposed circuit works with a supply voltage of 0.55V, and generates a 286mV reference voltage with a temperature coefficient of 59ppm/°C. The circuit takes 413nA current from 0.55V supply and occupies 0.00986mm2 of active area.
Hayatleh K, Zourob S, Nagulapalli R, et al., 2018, A High-Performance Skin Impedance Measurement Circuit for Biomedical Applications, Journal of Circuits, Systems and Computers, ISSN: 0218-1266
© 2019 World Scientific Publishing Company. This paper describes a high-performance impedance measurement circuit for the application of skin impedance measurement in the early detection of skin cancer. A CMRR improvement technique has been adopted for OTAs to reduce the impact of high-frequency common mode interference. A modified three-OTA instrumentation amplifier (IA) has been proposed to help with the impedance measurement. Such systems offer a quick, noninvasive and painless procedure, thus having considerable advantages over the currently used approach, which is based upon the testing of a biopsy sample. The sensor has been implemented in 65nm CMOS technology and post-layout simulations confirm the theoretical claims we made and sensor exhibits sensitivity. Circuit consumes 45uW from 1.5V power supply. The circuit occupies 0.01954mm2 silicon area.
Nagulapalli R, Hayatleh K, Barker S, et al., 2018, A High Value, Linear and Tunable CMOS Pseudo-Resistor for Biomedical Applications, Journal of Circuits, Systems and Computers, ISSN: 0218-1266
© 2019 World Scientific Publishing Company. A subthreshold MOS-based pseudo-resistor featuring a very high value and ultra-low distortion is proposed. A bandpass neural amplifier with a very low high-pass cutoff frequency is designed, to demonstrate the linearity of the proposed resistor. A BJT less CTAT current generator has been introduced to minimize the temperature drift of the resistor and make tuning easier. The standalone resistor has achieved 0.5% better linearity and a 12% improved temperature coefficient over the existing architectures. A neural amplifier has been designed with the proposed resistor as a feedback element. It demonstrated 31dB mid-band gain and a low-pass cutoff frequency of 0.85Hz. The circuit operates from a 1V supply and draws 950nA current at room temperature.
Hernandez B, Herrero P, Rawson TM, et al., 2018, Enhancing antimicrobial surveillance: an automated, dynamic and interactive approach, 18th International Congress on Infectious Disease, Publisher: Elsevier, Pages: 122-122, ISSN: 1201-9712
Rodriguez-Manzano J, Chia PY, Yeo TW, et al., 2018, Improving Dengue Diagnostics and Management Through Innovative Technology (vol 20, 25, 2018), CURRENT INFECTIOUS DISEASE REPORTS, Vol: 20, ISSN: 1523-3847
Rodriguez-Manzano J, Ying Chia P, Wen Yeo T, et al., 2018, Improving Dengue diagnostics and management through innovative technology, Current Infectious Disease Reports, Vol: 20, ISSN: 1534-3146
Purpose of Review:Dengue continues to be a major global public health threat. Symptomatic infections can cause a spectrum of disease ranging from a mild febrile illness to severe and potentially life-threatening manifestations. Management relies on supportive treatment with careful fluid replacement. The purpose of this review is to define the unmet needs and challenges in current dengue diagnostics and patient monitoring and outline potential novel technologies to address these needs.Recent Findings:There have been recent advances in molecular and point-of-care (POC) diagnostics as well as technologies including wireless communication, low-power microelectronics, and wearable sensors that have opened up new possibilities for management, clinical monitoring, and real-time surveillance of dengue.Summary:Novel platforms utilizing innovative technologies for POC dengue diagnostics and wearable patient monitors have the potential to revolutionize dengue surveillance, outbreak response, and management at population and individual levels. Validation studies of these technologies are urgently required in dengue-endemic areas.
Yu L-S, Yu L-S, Moser N, et al., 2018, Engineering rapid and sensitive electronic diagnostics for dengue and Zika viruses, Publisher: ELSEVIER SCI LTD, Pages: 166-166, ISSN: 1201-9712
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Rawson TM, Gowers S, Rogers M, et al., 2018, Towards a minimally invasive device for continuous monitoring of beta-lactam antibiotics, Publisher: ELSEVIER SCI LTD, Pages: 109-109, ISSN: 1201-9712
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Moniri A, Rodriguez-Manzano J, Georgiou P, 2018, A framework for analysis of real-time nucleic acid amplification data using novel multidimensional standard curves
<jats:title>ABSTRACT</jats:title><jats:p>Research into improving methods for absolute quantification of nucleic acids using standard curves has plateaued despite its positive, far-reaching impact on biomedical applications and clinical diagnostics. Currently, the mathematics involved in this mature area is restricted by the simplicity of conventional standard curves such as the gold standard cycle-threshold (<jats:italic>C<jats:sub>t</jats:sub></jats:italic>) method. Here, we propose a novel framework that expands current methods into multidimensional space and opens the door for more complex mathematical techniques, signal processing and machine learning to be implemented. The heart of this work revolves around two new concepts: the multidimensional standard curve and its home - the feature space. This work has been validated using phage lambda DNA and standard qPCR instruments. We show that the capabilities of standard curves can be extended in order to simultaneously: enhance absolute quantification, detect outliers and provide insights into the intersection between molecular biology and amplification data. This work and its vision aims to maximise the information extracted from amplification data using current instruments without increasing the cost or complexity of existing diagnostic settings.</jats:p>
Chen J, Li K, Herrero P, et al., 2018, Dilated recurrent neural network for short-time prediction of glucose concentration, 3rd International Workshop on Knowledge Discovery in Healthcare Data co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, Pages: 69-73, ISSN: 1613-0073
Diabetes is one of the diseases affecting 415 million people in the world. Developing a robust blood glucose (BG) prediction model has a profound influence especially important for the diabetes management. Subjects with diabetes need to adjust insulin doses according to the blood glucose levels to maintain blood glucose in a target range. An accurate glucose level prediction is able to provide subjects with diabetes with the future glucose levels, so that proper actions could be taken to avoid short-term dangerous consequences or long-term complications. With the developing of continuous glucose monitoring (CGM) systems, the accuracy of predicting the glucose levels can be improved using the machine learning techniques. In this paper, a new deep learning technique, which is based on the Dilated Recurrent Neural Network (DRNN) model, is proposed to predict the future glucose levels for prediction horizon (PH) of 30 minutes. And the method also can be implemented in real-time prediction as well. The result reveals that using the dilated connection in the RNN network, it can improve the accuracy of short-time glucose predictions significantly (RMSE = 19.04 in the blood glucose level prediction (BGLP) on and only on all data points provided).
Zhu T, Li K, Herrero P, et al., 2018, A deep learning algorithm for personalized blood glucose prediction, 3rd International Workshop on Knowledge Discovery in Healthcare Data co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018, Pages: 64-78, ISSN: 1613-0073
A convolutional neural network (CNN) model is presented to forecast the future glucose levels of the patients with type 1 diabetes. The model is a modified version of a recently proposed model called WaveNet, which becomes very useful in acoustic signal processing. By transferring the task into a classification problem, the model is mainly built by casual dilated CNN layers and employs fast WaveNet algorithms. The OhioT1DM dataset is the source of the four input fields: glucose levels, insulin events, carbohydrate intake and time index. The data is fed into the network along with the targets of the glucose change in 30 minutes. Several pre-processing approaches such as interpolation, combination and filtering are used to fill up the missing data in the training sets, and they improve the performance. Finally, we obtain the predictions of the testing dataset and evaluate the results by the root mean squared error (RMSE). The mean value of the best RMSE of six patients is 21.72.
Güemes A, Georgiou P, 2018, Review of the role of the nervous system in glucose homoeostasis and future perspectives towards the management of diabetes, Bioelectronic Medicine, Vol: 4, ISSN: 2332-8886
Diabetes is a disease caused by a breakdown in the glucose metabolic process resulting in abnormal blood glucose fluctuations. Traditionally, control has involved external insulin injection in response to elevated blood glucose to substitute the role of the beta cells in the pancreas which would otherwise perform this function in a healthy individual. The central nervous system (CNS), however, also plays a vital role in glucose homoeostasis through the control of pancreatic secretion and insulin sensitivity which could potentially be used as a pathway for enhancing glucose control. In this review, we present an overview of the brain regions, peripheral nerves and molecular mechanisms by which the CNS regulates glucose metabolism and the potential benefits of modulating them for diabetes management. Development of technologies to interface to the nervous system will soon become a reality through bioelectronic medicine and we present the emerging opportunities for the treatment of type 1 and type 2 diabetes.
Rawson T, Charani E, Moore L, et al., 2018, Exploring the use of C-Reactive Protein to Estimate the Pharmacodynamics of Vancomycin, Therapeutic Drug Monitoring, Vol: 40, Pages: 315-321, ISSN: 0163-4356
BackgroundC-reactive protein (CRP) pharmacodynamic (PD) models have the potential to provide adjunctive methods for predicting the individual exposure-response to antimicrobial therapy. We investigated CRP PD linked to a vancomycin PK model using routinely collected data from non-critical care adults in secondary care.MethodsPatients receiving intermittent intravenous vancomycin therapy in secondary care were identified. A two-compartment vancomycin PK model was linked to a previously described PD model describing CRP response. PK and PD parameters were estimated using a Non-Parametric Adaptive Grid technique. Exposure-response relationships were explored with vancomycin area-under-the-curve (AUC) and the index, AUC:EC50, fitted to CRP data using a sigmoidal Emax model. ResultsTwenty-nine individuals were included. Median age was 62 (21-97) years. Fifteen (52%) patients were microbiology confirmed. PK and PD models were adequately fitted (r2 0.83 and 0.82 respectively). There was a wide variation observed in individual Bayesian posterior EC50 estimates (6.95-48.55mg/L), with mean (SD) AUC:EC50 of 31.46 (29.22). AUC:EC50 was fitted to terminal CRP with AUC:EC50 >19 associated with lower CRP value at 96-120 hours of therapy (100mg/L vs. 44mg/L; p<0.01). ConclusionThe use of AUC:EC50 has the potential to provide in-vivo organism and host response data as an adjunct for in-vitro MIC data, which is currently used as the gold standard PD index for vancomycin therapy. This index can be estimated using routinely collected clinical data. Future work must investigate the role of AUC:EC50 in a prospective cohort and explore linkage with direct patient outcomes.
Panteli C, Georgiou P, Fobelets K, 2018, Performance improvement of commercial ISFET sensors using reactive ion etching, Microelectronic Engineering, Vol: 192, Pages: 61-65, ISSN: 0167-9317
Reactive Ion Etching (RIE) is used to improve the performance of commercial Complementary Metal Oxide Semiconductor (CMOS) Ion-Sensitive Field-Effect Transistors (ISFETs) by thinning the top passivation layers inherent of the CMOS fabrication process. Using a combination of O2 and SF6 in 50% ratio, both polyimide and Si3N4 layers are etched in one etching step. Etching for different times we find the right remaining layer thickness for best ISFET performance to be ∼1 μm of SiO2. The results show an increase in pH sensitivity of 125%, a 5700% increase in passivation capacitance and a 96% reduction in capacitive attenuation. The RIE etch recipe can be used on multi-project wafers (MPW) to boost CMOS sensor performance.
Sharma S, El-Laboudi A, Reddy M, et al., 2018, A pilot study in humans of microneedle sensor arrays for continuous glucose monitoring, Analytical Methods, Vol: 10, Pages: 2088-2095, ISSN: 1759-9660
Although subcutaneously implanted continuous glucose monitoring (CGM) devices have been shown to support diabetes self-management, their uptake remains low due to a combination of high manufacturing cost and limited accuracy and precision arising from their invasiveness. To address these points, minimally invasive, a solid microneedle array-based sensor for continuous glucose monitoring is reported here. These intradermal solid microneedle CGM sensors are designed for low cost manufacturing. The tolerability and performance of these devices is demonstrated through clinical studies, both in healthy volunteers and participants with type 1 diabetes (T1D). The geometry of these solid microneedles allows them to penetrate dermal tissue without the need for an applicator. The outer surface of these solid microneedles are modified as glucose biosensors. The microneedles sit in the interstitial fluid of the skin compartment and monitor real-time changes in glucose concentration. Optical coherence tomography measurements revealed no major axial movement of the microneedles in the tissue. No significant adverse events were observed and low pain scores were reported when compared to catheter insertion, deeming it safe for clinical studies in T1D. These amperometric sensors also yielded currents that tracked venous blood glucose concentrations, showing a clinically acceptable correlation. Studies in people with T1D gave a mean absolute relative difference (MARD) of 9% (with respect to venous blood glucose) with over 94% of the data points in the A and B zones of the Clarke error grid. These findings provide baseline data for further device development and a larger clinical efficacy and acceptability study of this microneedle intradermal glucose sensor in T1D.
Zeng J, Miscourides N, Georgiou P, 2018, A 128 x 128 Current-Mode Ultra-High Frame Rate ISFET Array for Ion Imaging, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
Moser N, Petrou L, Hu Y, et al., 2018, An ISFET Pixel with Integrated Trapped Charge Compensation using Temperature Feedback, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
El-Sharkawy M, Daniels J, Pesl P, et al., 2018, A Portable Low-Power Platform for Ambulatory Closed Loop Control of Blood Glucose in Type 1 Diabetes, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, ISSN: 0271-4302
Abdulwahab M, Moser N, Rodriguez Manzano J, et al., 2018, A CMOS Bio-Chip combining pH Sensing, Temperature Regulation and Electric Field Generation for DNA Detection and Manipulation, 2018 IEEE International Symposium on Circuits and Systems (ISCAS), ISSN: 2379-447X
Au A, Moser N, Rodriguez Manzano J, et al., 2018, Live demonstration: a mobile diagnostic system for rapid detection and tracking of infectious diseases, 2018 IEEE International Symposium on Circuits and Systems (ISCAS), ISSN: 2379-447X
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