0000000000178188
AUTHOR
M. Bataller
Hardware-efficient matrix inversion algorithm for complex adaptive systems
This work shows an FPGA implementation for the matrix inversion algebra operation. Usually, large matrix dimension is required for real-time signal processing applications, especially in case of complex adaptive systems. A hardware efficient matrix inversion procedure is described using QR decomposition of the original matrix and modified Gram-Schmidt method. This works attempts a direct VHDL description using few predefined packages and fixed point arithmetic for better optimization. New proposals for intermediate calculations are described, leading to efficient logic occupation together with better performance and accuracy in the vector space algebra. Results show that, for a relatively s…
Synchrony Analysis of Unipolar Cardiac Mapping during Ventricular Fibrillation
Ventricular Fibrillation (VF) is one of the main causes of death in developed countries. Recent studies have shown that fibrillation have a complex organization scheme. This work uses three measures of synchrony to characterize three groups of rabbit hearts. These groups consist of rabbits trained with physical exercise (N=7), untrained rabbits treated with a drug (N=13) and a control group of untrained rabbits (N=15). Cardiac mapping records were acquired using a 240-electrode array placed on left ventricle of isolated rabbit hearts, and VF was induced pacing at increasing rates. Two acquisitions were performed: maintained perfusion, and ischemic damage produced by an artery ligation. The …
Brain Activity Characterization Induced by Alcoholic Addiction: Spectral and Causality Analysis of Brain Areas Related to Control and Reinforcement of Impulsivity
Addiction to drugs generates modifications in the brain structure and its functions. In this work, an experimental model is described, using rats to characterize the brain activity induced by alcohol addiction. Four records were obtained using electrodes located in brain areas related to impulsivity control and reinforcement, i.e. the prelimbic (PL) and infralimbic (IL) cortex, together with the hippocampus (HPC). In the records, three main events related to the drinking action were selected: in the previous minute (T1), the first minute while drinking (T2) and the first minute after stopping drinking (T3).
Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation
This work presents the application of machine learning techniques to analyse the influence of physical exercise in the physiological properties of the heart, during ventricular fibrillation. To this end, different kinds of classifiers (linear and neural models) are used to classify between trained and sedentary rabbit hearts. The use of those classifiers in combination with a wrapper feature selection algorithm allows to extract knowledge about the most relevant features in the problem. The obtained results show that neural models outperform linear classifiers (better performance indices and a better dimensionality reduction). The most relevant features to describe the benefits of physical …
Ventricular fibrillation detection from ECG surface electrodes using different filtering techniques, window length and artificial neural networks
Medical personnel face many difficulties when diagnosing ventricular fibrillation (VF). Its correct diagnosis allows to decide the right medical treatment and, therefore, it is essential to tell it apart adequately from ventricular tachycardia (VT) and other arrhythmias. If the required therapy is not appropriate, the personnel could cause serious injuries or even induce VF. In this work, a diagnosis automatic system for the detection of VF through feature extraction was developed. To verify the validity of this method, an Artificial Neural Network (ANN) classifier was used. The ECG signals used were obtained from the MIT-BIH Malignant Ventricular Arrhythmia Database and AHA (2000 series) d…
Causal relationships between neurons of the nucleus incertus and the hippocampal theta activity in the rat
In recent years, a body of evidence has shown that the nucleus incertus (NI), in the dorsal tegmental pons, is a key node of the brainstem circuitry involved in hippocampal theta rhythmicity. Ascending reticular brainstem system activation evokes hippocampal theta rhythm with coupled neuronal activity in the NI. In a recent paper, we showed three populations of neurons in the NI with differential firings during hippocampal theta activation. The objective of this work is to better evaluate the causal relationship between the activity of NI neurons and the hippocampus during theta activation in order to further understand the role of the NI in the theta network. A Granger causality analysis w…
P and R Wave Detection in Complete Congenital Atrioventricular Block
Complete atrioventricular block (type III AVB) is characterized by an absence of P wave transmission to ventricles. This implies that QRS complexes are generated in an autonomous way and are not coordinated with P waves. This work introduces a new algorithm for the detection of P waves for this type of pathology using non-invasive electrocardiographic surface leads. The proposed algorithm is divided into three stages. In the first stage, the R waves located by a QRS detector are used to generate the RR series and time references for the other stages of the algorithm. In the second stage, the ventricular activity (QT segment) is removed by using an adaptive filter that obtains an averaged pa…
Feature selection for KNN classifier to improve accurate detection of subthalamic nucleus during deep brain stimulation surgery in Parkinson’s patients
The tremor and dystonia associated with Parkinson’s disease can be treated with deep brain stimulation (DBS) implanted into the subthalamic nucleus (STN). The accurate STN detection is a complex neurosurgeon task during a DBS surgery since a proper fixing of stimulating electrodes will impact on the patient’s future life. The brain electrical signals obtained with Micro Electrodes Register (MER) are acquired at different depths of the brain during DBS surgery to detect STN. In our previous work, we found good accuracy performance to improve the localization of STN using K-Nearest Neighbours (KNN) supervised learning algorithm. However, for real-time classification, it is essential to reduce…
High performance hardware correlation coefficient assessment using programmable logic for ECG signals
Abstract Correlation coefficient is frequently used to obtain cardiac rhythm by peak estimation and appreciate differences in the signal compared to a pattern. This work focuses on the description of a real-time correlation assessment procedure. Applied to electrocardiogram (ECG) signals, a new correlation value is obtained every new sample and pulse detection information is provided. The ECG pattern is internally stored and can be changed when desired. This procedure is useful in Systems on Chip implementation and can be applied to design compact ECG monitoring systems consisting on a system on chip where programmable logic offloads the main processor. A Xilinx FPGA device has been used fo…
Analysis of the influence of parasympathetic postganglionic neurons on cardiac response in Ventricular Fibrillation
Physical training modifies the sympathetic-vagal balance of autonomic nervous system. Previous studies have shown that such training also produces intrinsic modifications of cardiac electrophysiological properties in isolated heart during Ventricular Fibrillation (VF). Ten NZW trained rabbits were studied to test if the modifications are related to the activity of postganglionic parasympathetic neurons. Two records per subject were acquired during VF: before (G1) and after (G2) the infusion of atropine to inhibit the activity of neurons. Mapping records were obtained using a 240-channel electrode array located in the left ventricle of isolated heart (perfused by Langendorff system). VF was …
BioLab: An Educational Tool for Signal Processing Training in Biomedical Engineering
This paper introduces and evaluates BioLab, a tool for teaching biosignal processing. BioLab has been used in the biomedical engineering module that is given in the second semester of the fifth year of the electronic engineering degree at the University of Valencia, Spain. This module and its correspondent curricular pathway are also reviewed. BioLab allows the results obtained with digital processing techniques to be shown interactively in the theory classes, and it also provides support in laboratory sessions. The graphic interface of BioLab simplifies its learning and use and provides access to processing and visualization functions by means of menus. The tool is based on Matlab since th…
Implementation of a new adaptive algorithm using fuzzy cost function and robust to impulsive noise
Adaptive filters are used in a wide range of applications such as noise cancellation, system identification, and prediction. One of the main problems for theses filters is the impulsive noise as it generates algorithm unstability. This work shows the development, simulation and hardware implementation of a new algorithm robust to impulsive noise. Hardware implementation becomes essential in many cases where a real time execution, reduced size, or low power system is needed. An efficient hardware architecture is proposed and different optimizations for size and speed are developed: no need for control state machine, reduced computation requirements due to simplifications, etc. Furthermore, t…