Carotid hemodynamic response to external pressure and comparison with induced-stenosis progression: a fluid-structure interaction study.

Non-invasive stenosis detection has always been difficult. A new concept of applying external pressure over the artery was compared with stenosis growth in this computational study. When stenosis develops, the artery constricts, obstructing blood flow in that area. Under external pressure, the constricted artery behaves similarly. The current fluid-structure interaction study compares the hemodynamic parameters of a stenosed artery and an artery subjected to external pressure. Significant similarities were discovered when the velocity profile and arterial displacement for both scenarios were compared. This study can be used to characterise stenosis experimentally while remaining non-invasive.

Measurement of Near infrared Spectroscopy based Biomarkers under in-vitro Ischemic stroke condition.

Near infrared spectroscopy (NIRS) is an optical method which has been used widely to measure the change in the blood chromophores. Abrupt change in blood chromophore viz, oxyhemoglobin [hbo2] and deoxyhemoglobin [hb] happens in ischemia stroke condition, which occurs due to impairment of the oxygenated compounds viz, oxygen and glucose. The current study presents measurement and analysis of near infrared spectroscopy (NIRS) based regional oxygenation level biomarkers Viz., change in regional blood volume index [Formula: see text] and change in regional oxygen saturation [Formula: see text]. To measure these NIRS biomarkers dynamic phantom has been designed in such a way that, it mimics the ischemic stroke condition in-vitro by continuously changing (decrease, increase) the oxygenation level of human blood sample in the closed loop arterial system of dynamic phantom. Continuous decline of the [Formula: see text] % and [Formula: see text] 5% has been observed of the average reading of the samples in an ischemic stroke condition, while 15% and 2% increment has been recorded in reversal of ischemic stroke condition, by increasing the oxygenation level of the arterial system. Correlation between biomarkers in ischemic stroke condition has been found strongly positive (r=56%) and regular residual percentage error in measurement has been measured which has found under 10%. Clinical Relevance- This help in understanding and characterizing the ischemic stroke. Biomarker's trend can be use for classification of stroke types.

Inverse neurovascular coupling and associated spreading depolarization models for traumatic brain injury.

The paper presents the mathematical model of cortical spreading depolarisation and its effect on inverse neurovascular coupling. The paper considers the potassium ion channels present in the neuron-astrocyte blood vascular network to access the role of potassium ions during spreading depolarisation and associated inverse neurovascular coupling. Simulation of our proposed mathematical model confirms the experimental results that an increase in concentration of potassium ions beyond 20mM in the perivascular space essentially leads to vasoconstriction and hence inverse neurovascular coupling. The propagatory nature of depolarizing potassium waves has been unraveled though our proposed mathematical model.

A Novel Near Infrared Spectroscopy Based Device for Albumin Estimation.

In this paper we have proposed a fluorescence based spectroscopy device which can be used to quantitatively estimate the amount of albumin that gets excreted out of our body. Albumin is a significant protein in bio-fluids and performs a wide range of metabolic functions. The dye that has been used as a fluorescent indicator for the presence of albumin in this study has been earlier tested with bovine serum albumin (BSA) and human serum albumin (HSA) with satisfactory results. The method is based on principle of fluorescence in near infrared range (NIR) of 700 to 850 nm by using a novel dye with the test mixture. The chosen near infrared range has a benefit of absence of the auto fluorescence of the bio-molecules present in urine other than the albumin molecules. The system consists of: light source, spectroscopic chamber, sensing and computational unit. The study shows the stability and reproducibility of device so as to avoid fluctuations of voltage and other undesirables. The optimization with bovine serum albumin and human serum albumin has been done and the device can sense as low as 100 nM concentration precisely and accurately.Clinical Relevance-The system being presented is intended for developing a low cost point of care testing device for determining albumin concentration in urine.

Computational analysis of NIRS and BOLD signal from neurovascular coupling with three neuron-system feedforward inhibition network.

Several neurological disorders occur due to hypoxic condition in brain arising from impairment of cerebral functionality, which can be controlled by neural stimulation driven vasoactive response mediated through biological response in astrocyte, a phenomenon known as neurovascular coupling. Brain can adjust with the problem of hypoxic condition by causing vasodilation with the help of this mechanism. To deduce the mechanism behind vasodilation of blood vessel caused by neuronal stimulus, current study articulates a mathematical model involving neuronal system feedforward inhibition network model (FFI) with two other functional components of neurovascular coupling, i.e. astrocyte and smooth muscle cell lining blood vessel. This study includes the neural inhibition network system where glutamatergic pyramidal neuron and GABAergic interneuron act antagonistically with each other. The proposed model successfully includes the implication of the inhibition system to design mathematical model for neurovascular coupling. Result of the proposed model shows that the increase in neuronal stimulus from 20 to 60 µA/cm2 has the ability to increase the vasodilatory activity of blood tissue vasculature. Oxygenation level and hemodynamic response due to input synaptic stimulation has been calculated by regional cerebral oxygenation level (rS02) and blood oxygen level dependent (BOLD) imaging signal which supports vasodilation of blood vessel with increase in synaptic input stimulus.

Design of NIRS Probe Based on Computational Model to Find Out the Optimal Location for Non-Invasive Brain Stimulation.

The paper presents a computational model to analyse the electric field distribution on the cerebral cortex during high definition transcranial direct current stimulation (HD-tDCS) technique. The current research aims to improve the focality in term of magnitude of electric field (norm [E]) and magnitude of current density (norm [J]) in the gyri and sulci of white matter. The proposed computational model is used to predict the magnitude of current density and magnitude of electric field distribution generated across the target region of cerebral cortex for specific small size 1 × 1 cm2 multi-electrode HD-tDCS configurations. The current works aims at optimizing the number of electrodes and current density for multielectrode HD-tDCS configuration and weak current intensity is obtained by calculating surface area and penetration depth of target region of cerebral cortex. In terms of surface area and penetration depth 4 × 1 HD-tDCS and 2 mA weak dc current configuration has been selected. The optimized 4 × 1 HD-tDCS configuration is placed on target location of the brain surface and the changes in the magnitude of current density and magnitude of electric field distribution is calculated at the different locations on brain surface including scalp surface, skull surface gray matter and white matter surface. The variation in magnitude electric field distribution is seen in the cerebrospinal fluid (CSF), gray and white matter surface of target cerebral cortex. Based on the insights received from the variation in the magnitude of current density and magnitude of electric field distribution, the design of an appropriate NIRS probe has been proposed to aid in non-invasive brain stimulation. Designed NIRS probe is based on distance of separation between source and photodetector to cover the affected area with 4 × 1 HD-tDCS technique and measurement sensitivity distribution at gray matter surface of cerebral cortex. The estimated percentage of pixel area of measurement sensitivity distribution is 17.094%, which confirm to cover the 7.9384% distributed pixel area in term of calculated magnitude of current density affected with 4 × 1 HD-tDCS configuration.

High-resolution detection of sustained ventricular and supraventricular tachycardia through FPGA-based fuzzy processing of ECG signal.

The paper presents a field-programmable gate array (FPGA)-based fast processing system with 12-channel high-resolution (24 bits) front-end for ECG signal processing. The implemented high-resolution data conversion makes the system suitable for recording of late potentials of the QRS complex in patients prone to sustained ventricular tachycardia. The system accepts ECG signals through 12 channels and then filtered to minimize baseline wander and power-line interference. The filter outputs are connected to 12 delta-sigma ADCs. The whole ADCs work synchronously at 8 kHz sampling frequency, and their output data are transferred to an FPGA that computes online on the digitized sample values in real time and ascertains whether the patient under study suffers from ventricular tachycardia or not. In order to ascertain the QRS complex accurately in the noisy ECG signal, fuzzy entropy of the sample values has been computed and provided as an input to inverse multiquadratic radial basis function neural network. Using the standard CSE ECG database, the algorithm performed highly effectively. The performance of the algorithm in respect of QRS detection with sensitivity of 99.83 % and accuracy of 99.7 % is achieved when tested using single-channel ECG with entropy criteria. The performance of the QRS detection system has been compared and found to be better than most of the QRS detection systems available in the literature. Using the system, 200 patients have been diagnosed with an accuracy of 99 %.

Accuracy enhancement in a fuzzy expert decision making system through appropriate determination of membership functions and its application in a medical diagnostic decision making system.

The paper attempts to improve the accuracy of a fuzzy expert decision making system by tuning the parameters of type-2 sigmoid membership functions of fuzzy input variables and hence determining the most appropriate type-1 membership function. The current work mathematically models the variability of human decision making process using type-2 fuzzy sets. Moreover, an index of accuracy of a fuzzy expert system has been proposed and determined analytically. It has also been ascertained that there exists only one rule in the rule base whose associated mapping for the ith linguistic variable maps to the same value as the maximum value of the membership function for the ith linguistic variable. The improvement in decision making accuracy was successfully verified in a medical diagnostic decision making system for renal diagnostic applications. Based on the accuracy estimations applied over a set of pathophysiological parameters, viz. body mass index, glucose, urea, creatinine, systolic and diastolic blood pressure, appropriate type-1 fuzzy sets of these parameters have been determined assuming normal distribution of type-1 membership function values in type-2 fuzzy sets. The type-1 fuzzy sets so determined have been used to develop an FPGA based smart processor. Using the processor, renal diagnosis of patients has been performed with an accuracy of 98.75%.

ASIC design of a digital fuzzy system on chip for medical diagnostic applications.

The paper presents the ASIC design of a digital fuzzy logic circuit for medical diagnostic applications. The system on chip under consideration uses fuzzifier, memory and defuzzifier for fuzzifying the patient data, storing the membership function values and defuzzifying the membership function values to get the output decision. The proposed circuit uses triangular trapezoidal membership functions for fuzzification patients' data. For minimizing the transistor count, the proposed circuit uses 3T XOR gates and 8T adders for its design. The entire work has been carried out using TSMC 0.35 µm CMOS process. Post layout TSPICE simulation of the whole circuit indicates a delay of 31.27 ns and the average power dissipation of the system on chip is 123.49 mW which indicates a less delay and less power dissipation than the comparable embedded systems reported earlier.