RF communication with implantable wireless device: effects of beating heart on performance of miniature antenna

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

Towards a Reconfigurable Sense-and-Stimulate Neural Interface Generating Biphasic Interleaved Stimulus

Published versio

Offset prediction for charge-balanced stimulus waveforms

Functional electrical stimulation with cuff electrodes involves the controlled injection of current into an electrically excitable tissue for sensory or motor rehabilitation. Some charge injected during stimulation is 'lost' at the electrode-electrolyte interface when the charge carrier is translated from an electron to an ion in the solution. The process of charge injection through chemical reactions can reduce electrode longevity and implant biocompatibility. Conventionally, the excess charge is minimized by complex hardware solutions, which are often not appropriate for robust long-term implantable solutions. Here, we present a method of waveform design that minimizes irrecoverable charge during continuous pulsing through the use of biphasic waveforms with unequally charged phases. We developed an equivalent electrical model of the electrode-electrolyte impedance based on the electrode's surface chemistry during psuedo-bipolar stimulation conditions. Simulations with the equivalent circuit determined the uncompensated charge to be a function of stimulus parameters. In vitro stimulation experiments in saline confirmed that we could preemptively compensate for the excess charge following biphasic stimulus waveforms. As a result, there was a 92% reduction in the pre-pulse potential after a pulse train with this new waveform design when compared to stimulation with conventional biphasic waveforms

A computational model for anti-cancer drug sensitivity prediction

Various methods have been developed to build models for predicting drug response in cancer treatment based on patient data through machine learning algorithms. Drug prediction models can offer better patient data classification, optimising sensitivity identification in cancer therapy for suitable drugs. In this paper, a computational model based on Deep Neural Networks has been designed for prediction of anti-cancer drug response based on genetic expression data using publicly available drug profiling datasets from Cancer Cell Line Encyclopedia (CCLE). The model consists of several parts, including continuous drug response prediction, discretization and a drug sensitivity result output. Regularization and compression of neuron connections is also implemented to make the model compact and efficient, outperforming other widely used algorithms, such as elastic net (EN), random forest (RF), support vector regression (SVR) and simple artificial neural network (ANN) in sensitivity analysis and predictive accuracy

Assessment of the feasibility of an ultra-low power, wireless digital patch for the continuous ambulatory monitoring of vital signs.

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 support existing clinical protocols and workflows

A simulation study of the combined thermoelectric extracellular stimulation of the sciatic nerve of the Xenopus laevis: the localized transient heat block

The electrical behavior of the Xenopus laevis nerve fibers was studied when combined electrical (cuff electrodes) and optical (infrared laser, low power sub-5 mW) stimulations are applied. Assuming that the main effect of the laser irradiation on the nerve tissue is the localized temperature increase, this paper analyzes and gives new insights into the function of the combined thermoelectric stimulation on both excitation and blocking of the nerve action potentials (AP). The calculations involve a finite-element model (COMSOL) to represent the electrical properties of the nerve and cuff. Electric-field distribution along the nerve was computed for the given stimulation current profile and imported into a NEURON model, which was built to simulate the electrical behavior of myelinated nerve fiber under extracellular stimulation. The main result of this study of combined thermoelectric stimulation showed that local temperature increase, for the given electric field, can create a transient block of both the generation and propagation of the APs. Some preliminary experimental data in support of this conclusion are also shown

A monolithic (Si) massively broadband non-reverberant monopole

Accepted versio

Iridium oxide based potassium sensitive microprobe with anti-fouling properties

Here, we present a new type of potassium sensor which possesses a combination of potassium sensing and anti-biofouling properties. Two major advancements were required to be developed with respect to the current technology; Firstly, design of surface linkers for this type of coating that would allow deposition of the potassiumselective coating on Iridium (Ir) wire or micro-spike surface for chronic monitoring for the first time. As this has never been done before, even for flat Ir surfaces, the material’s small dimensions and surface area render this challenging. Secondly, the task of transformation of the coated wire into a sensor. Here we develop and bench-test the electrode sensitivity to potassium and determine its specificity to potassium versus sodium interference. For this purpose we also present a novel characterisation platform which enables dynamic characterization of the sensor including step and sinusoidal response to analyte changes. The developed sensor shows good sensitivity (<1 mM concentrations of K+ ions) and selectivity (up to approximately 10 times more sensitive to K+ than Na+ concentration changes, depending on concentrations and ionic environment). In addition, the sensor displays very good mechanical properties for the small diameter involved (sub 150 μm), which in combination with anti-biofouling properties, renders it an excellent potential tool for the chemical monitoring of neural and other physiological activities using implantable devices

A Programmable Neural Interface for Investigating Arbitrary Stimulation Strategies

Accepted versio

Enhancing automatic closed-loop glucose control in type 1 diabetes with an adaptive meal bolus calculator - in silico evaluation under intra- day variability

[EN] Background and Objective: Current 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. Methods: In 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. Results: Overall, 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; percentage time in target [70, 180] mg/dl, 82.0 ± 7.0 vs. 89.5 ± 4.2; percentage time above target 17.7 ± 7.0 vs. 10.2 ± 4.1. Adolescents: mean glucose 158.2 ± 21.4 vs. 140.5 ± 13.0 mg/dl; percentage time in target, 65.9 ± 12.9 vs. 77.5 ± 12.2; percentage time above target, 31.7 ± 13.1 vs. 19.8 ± 10.2. Note that no increase in percentage time in hypoglycemia was observed.This project has been funded by the Welcome Trust.Herrero, P.; Bondía Company, J.; Adewuji, O.; Pesl, P.; El-Sharkawy, M.; Reddy, M.; Toumazou, C.... (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. 146:125-131. https://doi.org/10.1016/j.cmpb.2017.05.010S12513114