463 results found
Rawson TM, Hernandez B, Moore L, et al., 2019, Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study, Journal of Antimicrobial Chemotherapy, Vol: 74, Pages: 1108-1115, ISSN: 0305-7453
BackgroundInfection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood parameters on presentation to hospital.MethodsAn SML algorithm was developed to classify cases into infection versus no infection using microbiology records and six available blood parameters (C-reactive protein, white cell count, bilirubin, creatinine, ALT and alkaline phosphatase) from 160 203 individuals. A cohort of patients admitted to hospital over a 6 month period had their admission blood parameters prospectively inputted into the SML algorithm. They were prospectively followed up from admission to classify those who fulfilled clinical case criteria for a community-acquired bacterial infection within 72 h of admission using a pre-determined definition. Predictive ability was assessed using receiver operating characteristics (ROC) with cut-off values for optimal sensitivity and specificity explored.ResultsOne hundred and four individuals were included prospectively. The median (range) cohort age was 65 (21–98) years. The majority were female (56/104; 54%). Thirty-six (35%) were diagnosed with infection in the first 72 h of admission. Overall, 44/104 (42%) individuals had microbiological investigations performed. Treatment was prescribed for 33/36 (92%) of infected individuals and 4/68 (6%) of those with no identifiable bacterial infection. Mean (SD) likelihood estimates for those with and without infection were significantly different. The infection group had a likelihood of 0.80 (0.09) and the non-infection group 0.50 (0.29) (P < 0.01; 95% CI: 0.20–0.40). ROC AUC was 0.84 (95% CI: 0.76–0.91).ConclusionsAn SML algorithm was able to diagnose infection in individuals presenting to hospital using routinely available blood parameters.
Chen C-H, Karvela M, Sohbati M, et al., 2018, PERSON - Personalized Expert Recommendation System for Optimized Nutrition, IEEE Transactions on Biomedical Circuits and Systems, Vol: 12, Pages: 151-160, ISSN: 1932-4545
The rise of personalized diets is due to the emergence of nutrigenetics and genetic tests services. However, the recommendation system is far from mature to provide personalized food suggestion to consumers for daily usage. The main barrier of connecting genetic information to personalized diets is the complexity of data and the scalability of the applied systems. Aiming to cross such barriers and provide direct applications, a personalized expert recommendation system for optimized nutrition is introduced in this paper, which performs direct to consumer personalized grocery product filtering and recommendation. Deep learning neural network model is applied to achieve automatic product categorization. The ability of scaling with unknown new data is achieved through the generalized representation of word embedding. Furthermore, the categorized products are filtered with a model based on individual genetic data with associated phenotypic information and a case study with databases from three different sources is carried out to confirm the system.
Cork SC, Eftekhar A, Mirza KB, et al., 2018, Extracellular pH monitoring for use in closed-loop vagus nerve stimulation, Journal of Neural Engineering, Vol: 15, Pages: 1-11, ISSN: 1741-2552
Objective: Vagal nerve stimulation (VNS) has shown potential benefits for obesity treatment; however, current devices lack physiological feedback, which limit their efficacy. Changes in extracellular pH (pHe) have shown to be correlated with neural activity, but have traditionally been measured with glass microelectrodes, which limit their in vivo applicability. Approach. Iridium oxide has previously been shown to be sensitive to fluctuations in pH and is biocompatible. Iridium oxide microelectrodes were inserted into the subdiaphragmatic vagus nerve of anaesthetised rats. Introduction of the gut hormone cholecystokinin (CCK) or distension of the stomach was used to elicit vagal nerve activity. Main results. Iridium oxide microelectrodes have sufficient pH sensitivity to readily detect changes in pHe associated with both CCK and gastric distension. Furthermore, a custom-made Matlab script was able to use these changes in pHe to automatically trigger an implanted VNS device. Significance. This is the first study to show pHe changes in peripheral nerves in vivo. In addition, the demonstration that iridium oxide microelectrodes are sufficiently pH sensitive as to measure changes in pHe associated with physiological stimuli means they have the potential to be integrated into closed-loop neurostimulating devices.
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.
Cooke GS, Gurrala R, Harrison E, et al., 2016, Novel pH sensing semiconductor for point-of-care detection of HIV-1 viremia, Scientific Reports, Vol: 6, ISSN: 2045-2322
The timely detection of viremia in HIV-infected patients receiving antiviral treatment is key to ensuring effective therapy and preventing the emergence of drug resistance. In high HIV burden settings, the cost and complexity of diagnostics limit their availability. We have developed a novel complementary metal-oxide semiconductor (CMOS) chip based, pH-mediated, point-of-care HIV-1 viral load monitoring assay that simultaneously amplifies and detects HIV-1 RNA. A novel low-buffer HIV-1 pH-LAMP (loop-mediated isothermal amplification) assay was optimised and incorporated into a pH sensitive CMOS chip. Screening of 991 clinical samples (164 on the chip) yielded a sensitivity of 95% (in vitro) and 88.8% (on-chip) at >1000 RNA copies/reaction across a broad spectrum of HIV-1 viral clades. Median time to detection was 20.8 minutes in samples with >1000 copies RNA. The sensitivity, specificity and reproducibility are close to that required to produce a point-of-care device which would be of benefit in resource poor regions, and could be performed on an USB stick or similar low power device.
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 Technology & Therapeutics, Vol: 18, Pages: 487-493, ISSN: 1557-8593
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.
Zuliani 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: 1364-5528
This 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.
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
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
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, 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
Seechurn 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
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
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
Pesl P, Herrero P, Reddy M, et al., 2015, An Advanced Bolus Calculator for Type 1 Diabetes: System Architecture and Usability Results., IEEE Journal of Biomedical and Health Informatics, Vol: 20, Pages: 11-17, ISSN: 2168-2208
This paper presents the architecture and initial usability results of an advanced insulin bolus calculator for diabetes (ABC4D), which provides personalized insulin recommendations for people with diabetes by differentiating between various diabetes scenarios and automatically adjusting its parameters over time. The proposed platform comprises two main components: a smartphone-based patient platform allowing manual input of glucose and variables affecting blood glucose levels (e.g., meal carbohydrate content and exercise) and providing real-time insulin bolus recommendations; and a clinical revision platform to supervise the automatic adaptations of the bolus calculator parameters. The system implements a previously in silico validated bolus calculator algorithm based on case-based reasoning, which uses information from similar past events (i.e., cases) to suggest improved personalized insulin bolus recommendations and automatically learns from new events. Usability of ABC4D was assessed by analyzing the system usage at the end of a six-week pilot study (n = 10). Further feedback on the use of ABC4D has been obtained from each participant at the end of the study from a usability questionnaire. On average, each participant requested 115 ± 21 insulin recommendations, of which 103 ± 28 (90%) were accepted. The clinical revision software proposed a total of 754 case revisions, where 723 (96%) adaptations were approved by a clinical expert and updated in the patient platform.
Hernandez-Silveira M, Ahmed K, Ang SS, et al., 2015, Assessment of the feasibility of an ultra-low power, wireless digital patch for the continuous ambulatory monitoring of vital signs., BMJ Open, Vol: 5, Pages: e006606-e006606, ISSN: 2044-6055
BACKGROUND AND OBJECTIVES: Vital signs are usually recorded at 4-8 h intervals in hospital patients, and deterioration between measurements can have serious consequences. The primary study objective was to assess agreement between a new ultra-low power, wireless and wearable surveillance system for continuous ambulatory monitoring of vital signs and a widely used clinical vital signs monitor. The secondary objective was to examine the system's ability to automatically identify and reject invalid physiological data. SETTING: Single hospital centre. PARTICIPANTS: Heart and respiratory rate were recorded over 2 h in 20 patients undergoing elective surgery and a second group of 41 patients with comorbid conditions, in the general ward. OUTCOME MEASURES: Primary outcome measures were limits of agreement and bias. The secondary outcome measure was proportion of data rejected. RESULTS: The digital patch provided reliable heart rate values in the majority of patients (about 80%) with normal sinus rhythm, and in the presence of abnormal ECG recordings (excluding aperiodic arrhythmias such as atrial fibrillation). The mean difference between systems was less than ±1 bpm in all patient groups studied. Although respiratory data were more frequently rejected as invalid because of the high sensitivity of impedance pneumography to motion artefacts, valid rates were reported for 50% of recordings with a mean difference of less than ±1 brpm compared with the bedside monitor. Correlation between systems was statistically significant (p<0.0001) for heart and respiratory rate, apart from respiratory rate in patients with atrial fibrillation (p=0.02). CONCLUSIONS: Overall agreement between digital patch and clinical monitor was satisfactory, as was the efficacy of the system for automatic rejection of invalid data. Wireless monitoring technologies, such as the one tested, may offer clinical value when implemented as part of wider hospital systems that integrate and supp
Herrero P, Pesl P, Reddy M, et al., 2015, Advanced insulin bolus advisor based on run-to-run control and case-based reasoning, IEEE Journal of Biomedical and Health Informatics, Vol: 19, Pages: 1087-1096, ISSN: 2168-2194
This paper presents an advanced insulin bolus advisor for people with diabetes on multiple daily injections or insulin pump therapy. The proposed system, which runs on a smartphone, keeps the simplicity of a standard bolus calculator while enhancing its performance by providing more adaptability and flexibility. This is achieved by means of applying a retrospective optimization of the insulin bolus therapy using a novel combination of run-to-run (R2R) that uses intermittent continuous glucose monitoring data, and case-based reasoning (CBR). The validity of the proposed approach has been proven by in-silico studies using the FDA-accepted UVa-Padova type 1 diabetes simulator. Tests under more realistic in-silico scenarios are achieved by updating the simulator to emulate intrasubject insulin sensitivity variations and uncertainty in the capillarity measurements and carbohydrate intake. The CBR(R2R) algorithm performed well in simulations by significantly reducing the mean blood glucose, increasing the time in euglycemia and completely eliminating hypoglycaemia. Finally, compared to an R2R stand-alone version of the algorithm, the CBR(R2R) algorithm performed better in both adults and adolescent populations, proving the benefit of the utilization of CBR. In particular, the mean blood glucose improved from 166 ± 39 to 150 ± 16 in the adult populations (p = 0.03) and from 167 ± 25 to 162 ± 23 in the adolescent population (p = 0.06). In addition, CBR(R2R) was able to completely eliminate hypoglycaemia, while the R2R alone was not able to do it in the adolescent population.
Herrero P, Pesl P, Bondia J, et al., 2015, Method for automatic adjustment of an insulin bolus calculator: In silico robustness evaluation under intra-day variability, COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, Vol: 119, Pages: 1-8, ISSN: 0169-2607
Sohbati M, Toumazou C, 2015, Dimension and Shape Effects on the ISFET Performance, IEEE SENSORS JOURNAL, Vol: 15, Pages: 1670-1679, ISSN: 1530-437X
Herrero P, Chen Z, Bondia J, et al., 2015, INTERVAL-BASED MODEL PREDICTIVE CONTROL FOR AN ARTIFICIAL PANCREAS, Publisher: MARY ANN LIEBERT, INC, Pages: A99-A99, ISSN: 1520-9156
Reddy M, Herrero P, El Sharkawy M, et al., 2015, CLINICAL EVALUATION OF THE BIO-INSPIRED ARTIFICIAL PANCREAS (BIAP) WITHOUT MEAL ANNOUNCEMENT IN ADULTS WITH TYPE 1 DIABETES, Publisher: MARY ANN LIEBERT, INC, Pages: A45-A46, ISSN: 1520-9156
Pesl P, Herrero P, Reddy M, et al., 2015, ACCEPTABILITY OF A PATIENT AND CLINICAL PLATFORM OF AN ADVANCED BOLUS CALCULATOR FOR TYPE 1 DIABETES (ABC4D), Publisher: MARY ANN LIEBERT, INC, Pages: A130-A130, ISSN: 1520-9156
Reddy M, Pesl P, Xenou M, et al., 2015, CLINICAL SAFETY EVALUATION OF AN ADVANCED BOLUS CALCULATOR FOR TYPE 1 DIABETES (ABC4D), Publisher: MARY ANN LIEBERT, INC, Pages: A130-A131, ISSN: 1520-9156
Reddy M, Herrero P, El Sharkawy M, et al., 2015, METABOLIC CONTROL WITH THE BIO-INSPIRED ARTIFICIAL PANCREAS (BIAP) IN ADULTS WITH TYPE 1 DIABETES: A 24-HOUR RANDOMISED CONTROLLED CROSSOVER STUDY, Publisher: MARY ANN LIEBERT, INC, Pages: A20-A21, ISSN: 1520-9156
Paraskevopoulou SE, Eftekhar A, Kulasekeram N, et al., 2015, A Low-Noise Instrumentation Amplifier with DC Suppression for Recording ENG Signals, 2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), Pages: 2693-2696, ISSN: 1557-170X
Reddy M, Herrero P, El Sharkawy M, et al., 2014, Feasibility study of a bio-inspired artificial pancreas in adults with type 1 diabetes, Diabetes Technology and Therapeutics, Vol: 16, Pages: 550-557, ISSN: 1520-9156
Background: This study assesses proof of concept and safety of a novel bio-inspired artificial pancreas (BiAP) system in adults with type 1 diabetes during fasting, overnight, and postprandial conditions. In contrast to existing glucose controllers in artificial pancreas systems, the BiAP uses a control algorithm based on a mathematical model of β-cell physiology. The algorithm is implemented on a miniature silicon microchip within a portable hand-held device that interfaces the components of the artificial pancreas.Materials and Methods: In this nonrandomized open-label study each subject attended for a 6-h fasting study followed by a 13-h overnight and post-breakfast study on a separate occasion. During both study sessions the BiAP system was used, and microboluses of insulin were recommended every 5 min by the control algorithm according to subcutaneous sensor glucose levels. The primary outcome was percentage time spent in the glucose target range (3.9–10.0 mmol/L).Results: Twenty subjects (55% male; mean [SD] age, 44  years; duration of diabetes, 22  years; glycosylated hemoglobin, 7.4% [0.7%] [57 (7) mmol/mol]; body mass index, 25  kg/m2) participated in the fasting study, and the median (interquartile range) percentage time in target range was 98.0% (90.8–100.0%). Seventeen of these subjects then participated in the overnight/postprandial study, where 70.7% (63.9–77.4%) of time was spent in the target range and, reassuringly, 0.0% (0.0–2.3%) of time was spent in hypoglycemia (<3.9 mmol/L).Conclusions: The BiAP achieves safe glycemic control during fasting, overnight, and postprandial conditions.
Reddy M, Agha-Jaffar R, Herrero P, et al., 2014, The impact of glycaemic variability on quality of life in adults with type1 diabetes, Publisher: SPRINGER, Pages: S429-S429, ISSN: 0012-186X
Kalofonou M, Toumazou C, 2014, A Low Power Sub-μW Chemical Gilbert Cell for ISFET Differential Reaction Monitoring, IEEE Transactions on Biomedical Circuits and Systems, Pages: 1-1, ISSN: 1932-4545
This paper presents a low power current-mode method for monitoring differentially derived changes in pH from ion-sensitive field-effect transistor (ISFET) sensors, by adopting the Chemical Gilbert Cell. The fabricated system, with only a few transistors, achieves differential measurements and therefore drift minimisation of continuously recorded pH signals obtained from biochemical reactions such as DNA amplification in addition to combined gain tunability using only a single current. Experimental results are presented, demonstrating the capabilities of the front-end at a microscopic level through integration in a lab-on-chip (LoC) setup combining a microfluidic assembly, suitable for applications that require differential monitoring in small volumes, such as DNA detection where more than one gene needs to be studied. The system was designed and fabricated in a typical 0.35 μm CMOS process with the resulting topology achieving good differential pH sensitivity with a measured low power consumption of only 165 nW due to weak inversion operation. A tunable gain is demonstrated with results confirming 15.56 dB gain at 20 nA of ISFET bias current and drift reduction of up to 100 times compared to a single-ended measurement is also reported due to the differential current output, making it ideal for robust, low-power chemical measurement.
Murphy OH, Borghi A, Bahmanyar MR, et al., 2014, RF communication with implantable wireless device: effects of beating heart on performance of miniature antenna, Healthcare Technology Letters, Vol: 1, Pages: 51-55, ISSN: 2053-3713
The frequency response of an implantable antenna is key to the performance of a wireless implantable sensor. If the antenna detunes significantly, there are substantial power losses resulting in loss of accuracy. One reason for detuning is because of a change in the surrounding environment of an antenna. The pulsating anatomy of the human heart constitutes such a changing environment, so detuning is expected but this has not been quantified dynamically before. Four miniature implantable antennas are presented (two different geometries) along with which are placed within the heart of living swine the dynamic reflection coefficients. These antennas are designed to operate in the short range devices frequency band (863-870 MHz) and are compatible with a deeply implanted cardiovascular pressure sensor. The measurements recorded over 27 seconds capture the effects of the beating heart on the frequency tuning of the implantable antennas. When looked at in the time domain, these effects are clearly physiological and a combination of numerical study and posthumous autopsy proves this to be the case, while retrospective simulation confirms this hypothesis. The impact of pulsating anatomy on antenna design and the need for wideband implantable antennas is highlighted.
Trantidou T, Tariq M, Terracciano CM, et al., 2014, Parylene C-Based Flexible Electronics for pH Monitoring Applications, Sensors, Vol: 14, Pages: 11629-11639, ISSN: 1424-8239
Emerging materials in the field of implantable sensors should meet the needs for biocompatibility; transparency; flexibility and integrability. In this work; we present an integrated approach for implementing flexible bio-sensors based on thin Parylene C films that serve both as flexible support substrates and as active H+ sensing membranes within the same platform. Using standard micro-fabrication techniques; a miniaturized 40-electrode array was implemented on a 5 μm-thick Parylene C film. A thin capping film (1 μm) of Parylene on top of the array was plasma oxidized and served as the pH sensing membrane. The sensor was evaluated with the use of extended gate discrete MOSFETs to separate the chemistry from the electronics and prolong the lifetime of the sensor. The chemical sensing array spatially maps the local pH levels; providing a reliable and rapid-response (<5 s) system with a sensitivity of 23 mV/pH. Moreover; it preserves excellent encapsulation integrity and low chemical drifts (0.26–0.38 mV/min). The proposed approach is able to deliver hybrid flexible sensing platforms that will facilitate concurrent electrical and chemical recordings; with application in real-time physiological recordings of organs and tissues.
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