Results
- Showing results for:
- Reset all filters
Search results
-
Journal articleSohbati M, Toumazou C, 2015,
Dimension and Shape Effects on the ISFET Performance
, IEEE SENSORS JOURNAL, Vol: 15, Pages: 1670-1679, ISSN: 1530-437X- Author Web Link
- Cite
- Citations: 31
-
Conference paperHerrero 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 -
Conference paperReddy 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- Author Web Link
- Cite
- Citations: 1
-
Conference paperPesl 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 -
Conference paperReddy 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 -
Journal articleKaufman N, Bian RR, 2015,
Using Health Information Technology to Prevent and Treat Diabetes
, DIABETES TECHNOLOGY & THERAPEUTICS, Vol: 17, Pages: S53-S66, ISSN: 1520-9156 -
Conference paperWilliams I, Luan S, Jackson A, et al., 2015,
Live Demonstration: A Scalable 32-Channel Neural Recording and Real-time FPGA Based Spike Sorting System
, 11th IEEE Annual Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 187-187, ISSN: 2163-4025- Author Web Link
- Cite
- Citations: 1
-
Journal articleParaskevopoulou 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- Author Web Link
- Cite
- Citations: 3
-
Conference paperLauteslager T, Nicolaou N, Lande TS, et al., 2015,
Functional neuroimaging using UWB impulse radar: A feasibility study.
, Publisher: IEEE, Pages: 1-4 -
Conference paperDemarchou E, Georgiou J, Nicolaou N, et al., 2014,
Anesthetic-induced changes in EEG activity: a graph theoretical approach
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Pages: 45-48The dynamic brain networks forming during wakefulness and anesthetic-induced unconsciousness are investigated using time-delayed correlation and graph theoretical measures. Electrical brain activity (EEG) from 10 patients under propofol anesthesia during routine surgery is characterized using the shortest path length, λ, and clustering, c, extracted from time delayed correlation. An increase in λ and c during anesthesiareveals disruption of long-range connections and emergence of more localized neighborhoods. These changes were not a result of volume conduction, as were based on time-delayed correlation. Our observations are in line with theories of anesthetic action and support the use of graph theoretic measures to study emerging brain networks during wakefulness and anesthesia.
-
Conference paperKalofonou M, Toumazou C, 2014,
Early screening of breast cancer recurrence by monitoring DNA methylation based biomarkers using semiconductor technology
, MEC Annual Meeting and Bioengineering14, Cancer Engineering and TechnologiesBreast cancer is one of the most common cancer types in women, with 1 in 8 women having a lifetime risk of incidence. From the cases of primary breast cancer, more than 30% of diagnosed and treated cases will most likely lead to a metastasis, also known as cancer recurrence, within a period of 5-15 years from time of first diagnosis, dependent on the aggressiveness and rate of disease progression. From the stage of first detection of primary breast cancer to the point of a metastatic recurrence, certain tumour-specific genetic and epigenetic changes occur. The use of epigenetic markers, specifically DNA methylation, as a biomarker for cancer has shown great potential due to its role in the initiation, progression and recurrence of the disease. Given that the time of the event of a metastasis can vary from the moment of initial diagnosis, the use of markers that could monitor tumour progression by detecting tumour-specific DNA methylation based changes would provide significant insight in estimating the risk of recurrence, so that the right therapy is being addressed at the right time, in a more personalised way. Current screening methods of breast cancer have shown that more newly developed/recurred breast cancer cases can now be diagnosed but with the risk of more false-positive findings which could further lead to unnecessary treatment due to the possible misinterpretation of the imaging result (low/high risk lesions). Studies have shown that DNA methylation patterns found in blood can be used as reliable markers for distinguishing breast cancer patients from healthy subjects as well as for assessing the progression of breast cancer after therapy. Detection of DNA methylation changes could therefore offer a very promising alternative approach to early screening of breast cancer recurrence, providing with a more individualised clinical assessment and management of cancer as a chronic disease. A Point-of-Care system using the methylation profile of carefully selecte
-
Journal articleReddy 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: 1520-9156Background: 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 [10] years; duration of diabetes, 22 [12] years; glycosylated hemoglobin, 7.4% [0.7%] [57 (7) mmol/mol]; body mass index, 25 [4] 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.
-
Conference paperReddy 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- Author Web Link
- Cite
- Citations: 7
-
Journal articleKalofonou 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: 1932-4545This 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.
-
Journal articleMurphy 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: 2053-3713The 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.
-
Journal articleParaskevopoulou SE, Wu D, Eftekhar A, et al., 2014,
Hierarchical Adaptive Means (HAM) Clustering for Hardware-Efficient, Unsupervised and Real-time Spike Sorting.
, Journal of Neuroscience Methods, Vol: 235, Pages: 145-156, ISSN: 1872-678XThis work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation.
-
Journal articleTrantidou T, Tariq M, Terracciano CM, et al., 2014,
Parylene C-Based Flexible Electronics for pH Monitoring Applications
, Sensors, Vol: 14, Pages: 11629-11639, ISSN: 1424-8239Emerging 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.
-
Journal articleLuan S, Williams I, Constandinou TG, et al., 2014,
Neuromodulation: present and emerging methods
, Frontiers of Neuroengineering, Vol: 7, ISSN: 1662-6443Neuromodulation has wide ranging potential applications in replacing impaired neural function (prosthetics), as a novel form of medical treatment (therapy), and as a tool for investigating neurons and neural function (research). Voltage and current controlled electrical neural stimulation (ENS) are methods that have already been widely applied in both neuroscience and clinical practice for neuroprosthetics. However, there are numerous alternative methods of stimulating or inhibiting neurons. This paper reviews the state-of-the-art in ENS as well as alternative neuromodulation techniques - presenting the operational concepts, technical implementation and limitations - in order to inform system design choices.
-
Journal articleWilliams I, Constandinou TG, 2014,
Computationally Efficient Modelling of Proprioceptive Signals in the Upper Limb for Prostheses: a Simulation Study
, Frontiers in Neuroscience, Vol: 8, Pages: 1-13Accurate models of proprioceptive neural patterns could one day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimisation) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modelling. This paper uses and proposes a number of approximations and optimisations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed.
-
Journal articleEftekhar A, Juffali W, El-Imad J, et al., 2014,
Ngram-derived Pattern Recognition for the Detection and Prediction of Epileptic Seizures
, PLOS One, Vol: 9, Pages: 1-15This work presents a new method that combines symbol dynamics methodologies with an Ngram algorithm for the detection and prediction of epileptic seizures. The presented approach specifically applies Ngram-based pattern recognition, after data pre-processing, with similarity metrics, including the Hamming distance and Needlman-Wunsch algorithm, for identifying unique patterns within epochs of time. Pattern counts within each epoch are used as measures to determine seizure detection and prediction markers. Using 623 hours of intracranial electrocorticogram recordings from 21 patients containing a total of 87 seizures, the sensitivity and false prediction/detection rates of this method are quantified. Results are quantified using individual seizures within each case for training of thresholds and prediction time windows. The statistical significance of the predictive power is further investigated. We show that the method presented herein, has significant predictive power in up to 100% of temporal lobe cases, with sensitivities of up to 70–100% and low false predictions (dependant on training procedure). The cases of highest false predictions are found in the frontal origin with 0.31–0.61 false predictions per hour and with significance in 18 out of 21 cases. On average, a prediction sensitivity of 93.81% and false prediction rate of approximately 0.06 false predictions per hour are achieved in the best case scenario. This compares to previous work utilising the same data set that has shown sensitivities of up to 40–50% for a false prediction rate of less than 0.15/hour.
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.
Contact us
Centre for Bio-Inspired Technology
Imperial College London
Bessemer Building
South Kensington
SW7 2AZ, UK
Tel: +44 (0)207 594 0701
Fax: +44 (0)207 594 0704
E-mail: bioinspired@imperial.ac.uk