Publications
Results
- Showing results for:
- Reset all filters
Search results
-
Journal articleReddy 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: 487-493BACKGROUND: 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.
-
Conference paperKoutsos A, Kalofonou M, Sohbati M, et al., 2016,
Epigenetic-IC: A fully integrated sensing platform for epigenetic reaction monitoring
, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 325-328, ISSN: 2379-447XThis paper presents a pH-based System-on-Chip DNA methylation quantification platform for real time monitoring of DNA methylation ratio in target genes. The architecture forms a novel autonomous system, capable of providing diagnostic information on the progression of a disease, notably cancer. The system is equipped with drift and trapped charge compensation schemes based on differential measurements and an auto-calibration algorithm. The simulated system in 0.35μm CMOS technology achieves a power consumption of 0.997mW, with a DNA methylation ratio output sensitivity of 0.1%. The ISFET-based detection platform occupies a total of 901um2 and allows the calculation of DNA methylation ratio in pH-monitored DNA methylation based reactions.
-
Conference paperNicolaou N, Constandinou TG, 2016,
Phase-Amplitude Coupling during propofol-induced sedation: an exploratory approach
, FENS Forum of Neuroscience, Publisher: FENS -
Conference paperLuan S, Williams I, de Carvalho F, et al., 2016,
Next Generation Neural Interfaces for low-power multichannel spike sorting
, FENS Forum of Neuroscience, Publisher: FENS -
Journal articleNicolaou N, Constandinou TG, 2016,
A nonlinear causality estimator based on Non-Parametric Multiplicative Regression
, Frontiers in Neuroinformatics, Vol: 10, ISSN: 1662-5196Causal prediction has become a popular tool for neuroscience applications, as it allows the study of relationships between different brain areas during rest, cognitive tasks or brain disorders. We propose a nonparametric approach for the estimation of nonlinear causal prediction for multivariate time series. In the proposed estimator, C-NPMR, Autoregressive modelling is replaced by Nonparametric Multiplicative Regression (NPMR). NPMR quantifies interactions between a response variable (effect) and a set of predictor variables (cause); here, we modified NPMR for model prediction. We also demonstrate how a particular measure, the sensitivity Q, could be used to reveal the structure of the underlying causal relationships. We apply C-NPMR on artificial data with known ground truth (5 datasets), as well as physiological data (2 datasets). C-NPMR correctly identifies both linear and nonlinear causal connections that are present in the artificial data, as well as physiologically relevant connectivity in the real data, and does not seem to be affected by filtering. The Sensitivity measure also provides useful information about the latent connectivity.The proposed estimator addresses many of the limitations of linear Granger causality and other nonlinear causality estimators. C-NPMR is compared with pairwise and conditional Granger causality (linear) and Kernel-Granger causality (nonlinear). The proposed estimator can be applied to pairwise or multivariate estimations without any modifications to the main method. Its nonpametric nature, its ability to capture nonlinear relationships and its robustness to filtering make it appealing for a number of applications.
-
Conference paperBarsakcioglu DY, Constandinou TG, 2016,
A 32-Channel MCU-Based Feature Extraction and Classification for Scalable on-Node Spike Sorting
, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 1310-1313This paper describes a new hardware-efficientmethod and implementation for neural spike sorting basedon selection of a channel-specific near-optimal subset of fea-tures given a larger predefined set. For each channel, real-time classification is achieved using a simple decision matrixthat considers the features that provide the highest separabilitydetermined through off-line training. A 32-channel system for on-line feature extraction and classification has been implementedin an ARM Cortex-M0+ processor. Measured results of thehardware platform consumes 268 W per channel during spikesorting (includes detection). The proposed method provides atleast x10 reduction in computational requirements compared toliterature, while achieving an average classification error of lessthan 10% across wide range of datasets and noise levels.
-
Conference paperElia M, Leene L, Constandinou TG, 2016,
Continuous-Time Micropower Interface for Neural Recording Applications
, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 534-637This paper presents a novel amplifier architectureintended for low power neural recording applications. By usingcontinuous-time signal representation, the proposed topologypredominantly leverages digital topologies taking advantage ofefficient techniques used in time domain systems. This includeshigher order feedback dynamics that allow direct analoguesignal quantization and near ideal integrator structures for noiseshaping. The system implemented in 0.18 μ m standard CMOSdemonstrates the capability for low noise instrumentation witha bandwidth of 6 kHz and highly linear full dynamic range.Simulation results indicate 1.145 μW budget from 0.5 V supplyvoltage with an input referred thermal noise of 7.7 μVrms.
-
Conference paperLiu Y, Pereira J, Constandinou TG, 2016,
Clockless Continuous-Time Neural Spike Sorting: Method, Implementation and Evaluation
, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 538-541In this paper, we present a new method for neuralspike sorting based on Continuous Time (CT) signal processing.A set of CT based features are proposed and extracted fromCT sampled pulses, and a complete event-driven spike sortingalgorithm that performs classification based on these features isdeveloped. Compared to conventional methods for spike sorting,the hardware implementation of the proposed method does notrequire any synchronisation clock for logic circuits, and thusits power consumption depend solely on the spike activity. Thishas been implemented using a variable quantisation step CTanalogue to digital converter (ADC) with custom digital logicthat is driven by level crossing events. Simulation results usingsynthetic neural data shows a comparable accuracy comparedto template matching (TM) and Principle Components Analysis(PCA) based discrete sampled classification.
-
Journal articleWoods S, Constandinou TG, 2016,
A compact targeted drug delivery mechanism for a next generation wireless capsule endoscope
, Journal of Micro-Bio Robotics, Vol: 11, Pages: 19-34, ISSN: 2194-6426This paper reports a novel medication release and delivery mechanism as part of a next generation wireless capsule endoscope (WCE) for targeted drug delivery. This subsystem occupies a volume of only 17.9mm3 for the purpose of delivering a 1 ml payload to a target site of interest in the small intestinal tract. An in-depth analysis of the method employed to release and deliver the medication is described and a series of experiments is presented which validates the drug delivery system. The results show that a variable pitch conical compression spring manufactured from stainless steel can deliver 0.59 N when it is fully compressed and that this would be sufficient force to deliver the onboard medication.
-
Journal articleZuliani C, Ng FS, Alenda A, et al., 2016,
An array of individually addressable micro-needles for mapping pH distributions
, Analyst, Vol: 141, Pages: 4659-4666, ISSN: 1364-5528This work describes the preparation of an array of individually addressable pH sensitive microneedles which are sensitized by electrodepositing iridium oxide. The impact of the deposition potential, storage conditions and interferents on the sensor characteristics such as slope, offset, intra- and inter-batch reproducibility is investigated. The device may be a useful tool for carrying out direct pH measurements of soft and heterogeneous samples such as tissues and organs. For example, we demonstrated that the microneedle array can be employed for real-time mapping of the cardiac pH distribution during cycles of global ischemia and reperfusion.
-
Conference paperTroiani F, Nikolic K, Constandinou TG, 2016,
Optical Coherence Tomography for detection of compound action potential in Xenopus Laevis sciatic nerve
, SPIE Photonics West (BIOS)Due to optical coherence tomography (OCT) high spatial and temporal resolution, this technique could be used to observe the quick changes in the refractive index that accompany action potential. In this study we explorethe use of time domain Optical Coherence Tomography (TD-OCT) for real time action potential detection in ex vivo Xenopus Laevis sciatic nerve. TD-OCT is the easiest and less expensive OCT technique and, if successful indetecting real time action potential, it could be used for low cost monitoring devices. A theoretical investigation into the order of magnitude of the signals detected by a TD-OCT setup is provided by this work. A lineardependence between the refractive index and the intensity changes is observed and the minimum SNR for which the setup could work is found to be SNR = 2 x10⁴.
-
Journal articleGuven O, Eftekhar A, Kindt W, et al., 2016,
Computationally-efficient realtime interpolation algorithm for non-uniform sampled biosignals
, Healthcare Technology Letters, Vol: 3, Pages: 105-110, ISSN: 2053-3713This letter presents a novel, computationally-efficient interpolation method that has been optimised for use in ECG baseline drift removal. In our previous work 3 isoelectric baseline points per heart beat are detected, and here utilised as interpolation points. As an extension from linear interpolation, our algorithm segments the interpolation interval and utilises different piecewise linear equations. Thus the algorithm produces a linear curvature that is computationally efficient while avoiding overshoots on nonuniform samples. The proposed algorithm is tested using sinusoids with different fundamental frequencies from 0.05Hz to 0.7Hz and also validated with real baseline wander data acquired from the MIT-BIH Noise Stress Database. The synthetic data results show an RMS error of 0.9μV (mean), 0.63μV (median) and 0.6μV (std. dev.) per heart beat on a 1mVp-p 0.1Hz sinusoid. On real data we obtain an RMS error of 10.9μV (mean), 8.5μV (median) and 9.0μV (std. dev.) per heart beat. Cubic spline interpolation and linear interpolation on the other hand shows 10.7μV, 11.6μV (mean), 7.8μV, 8.9μV(median) and 9.8μV, 9.3μV (std. dev.) per heart beat respectively.
-
Conference paperPesl 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 -
Conference paperPesl 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 -
Conference paperSeechurn S, Reddy M, Jugnee N, et al., 2016,
Does the addition of glucagon to a closed loop system impact on post exercise glycaemia?
, ATTD 2016 9th International Conference on Advanced Technologies & Treatments for Diabetes, Publisher: Mary Ann Liebert, Pages: A60-A60, ISSN: 1520-9156 -
Conference paperHerrero 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 -
Conference paperEl 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 -
Journal articleReddy 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 -
Journal articleHerrero 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- Author Web Link
- Cite
- Citations: 4
-
Conference paperMurphy O, Bahmanyar MR, McLeod CN, et al., 2016,
Beyond RF ablation other uses for RF within the body
, Pages: 1362-1364The use of high frequencies within the body is commonplace for treatment and imaging, but, other than a few examples very little exists in terms of RF sensors and for communication deep into the body. This paper will give an overview of an RF powered implantable blood pressure sensor for continuous monitoring and in doing so demonstrate the use of RF within the body.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.