Asma Ben Abdallah

Real time QRS complex detection using DFA and regular grammar

BackgroundThe sequence of Q, R, and S peaks (QRS) complex detection is a crucial procedure in electrocardiogram (ECG) processing and analysis. We propose a novel approach for QRS complex detection based on the deterministic finite automata with the addition of some constraints. This paper confirms that regular grammar is useful for extracting QRS complexes and interpreting normalized ECG signals. A QRS is assimilated to a pair of adjacent peaks which meet certain criteria of standard deviation and duration.ResultsThe proposed method was applied on several kinds of ECG signals issued from the standard MIT-BIH arrhythmia database. A total of 48 signals were used. For an input signal, several parameters were determined, such as QRS durations, RR distances, and the peaks’ amplitudes. σRR and σQRS parameters were added to quantify the regularity of RR distances and QRS durations, respectively. The sensitivity rate of the suggested method was 99.74% and the specificity rate was 99.86%. Moreover, the sensitivity and the specificity rates variations according to the Signal-to-Noise Ratio were performed.ConclusionsRegular grammar with the addition of some constraints and deterministic automata proved functional for ECG signals diagnosis. Compared to statistical methods, the use of grammar provides satisfactory and competitive results and indices that are comparable to or even better than those cited in the literature.

Grammar-based image segmentation and automatic area estimation

Image segmentation is an important task in the image processing and represents a very active research field such as on medical image processing. The aim of this work is to segment an image and make an automated area estimation based on grammar. The entity “language” will be projected to the entity “image” to perform structural analysis and parsing of the image. We achieve to define an image as a set of words based on an alphabet. An object is assimilated as a word recognized by an automaton. We will show how the idea of grammar-based segmentation is applied to synthetic and real problems of cardio-graphic image processing.

Spectral density variation mapping of cerebral waves by three-dimensional interpolation techniques

This work focuses on interpolation methods which are proposed as solutions to the EEG source localization. First, a low pass and a high pass filter were applied to the EEG signal in order to remove EEG artifacts. Then, classical interpolation techniques such as three‐dimensional (3D) K‐nearest neighbor and 3D spline were implemented. The major contribution of this article is to develop a new interpolation method called 3D multiquadratic technique which is based on the Euclidean distances between the electrodes. A substitution of the Euclidean distance by the corresponding arc length was realized to promote the 3D spherical multiquadratic interpolation. Based on measured EEG recordings from 19 electrodes mounted on the scalp, these interpolation methods (3D K‐nearest neighbor, 3D spline, 3D multiquadratic and spherical multiquadratic) were applied to EEG recordings of 15 healthy subjects at rest and with closed eyes. The aim of EEG interpolation is to reach the maximum of the spatial resolution of EEG mapping by predicting the brain activity distribution of 109 virtual points located on the scalp surface. The evaluation of the different interpolation methods was achieved by measuring the means of the normalized root mean squared error (NRMSE) and processing time. The results showed that the multiquadratic and 3D spline interpolation methods gave the minimum normalized root mean squared error, but the multiquadratic method was characterized by the minimal processing time compared with 3D K‐nearest neighbor, 3D spline, and 3D spherical multiquadratic methods. Finally, a Spectral density variation mapping of different cerebral waves (delta, theta, alpha and beta) with 128 electrodes was generated by applying the Fast Fourier Transform (FFT).

EEG potential mapping by 3D interpolation methods

We propose in this work two main interpolation methods (barycentric, spline) applicable to 3D EEG mapping. These 3D methods are used to interpolate scalp potential activity in order to obtain a more efficient spatiotemporal resolution of EEG mapping. Starting from 19 electrodes to generate the potential representations of patients having various behavioral states, we obtain a 3D potential representation of 128 electrodes thanks to the 3D interpolation methods. The evaluation of these algorithms is realized by calculating the normalized Root Mean Squared error (RMS).

Local deformation analysis in the heart left ventricle using the regional volume evolution

Finding an efficient method for the deformation analysis in the left ventricle of the heart (LV) is one of the major concerns in cardiac imaging. We propose in this paper a new approach aimed at specifying the affected area in the LV and based on the volume evolution computation for different regions using Gauss divergence theorem. This approach is validated with deformable surfaces synthesized from ellipsoidal model and real data obtained from myocardial scintigraphy imaging techniques. Experimental results show its ability to quantify and characterize the closed surface deformations of any organ data obtained from various medical imaging techniques.

A robust QRS complex detection using regular grammar and deterministic automata

Abstract A novel approach is proposed for medical analysis and clinical decision support of the Electrocardiogram (ECG) signals based on the deterministic finite automata (DFA) with the addition of some requirements. This paper proves regular grammar is effective in the extraction of QRS complex and interpretation of ECG signals. The DFA will be used to represent a normalized QRS complex as a sequence of negative and positive peaks. A QRS is considered as a set of adjacent peaks that satisfy certain criteria of standard deviation and duration. The proposed method is applied on several kinds of ECG signals collected from the standard MIT-BIH arrhythmia database. Several metrics are calculated including QRS durations, RR distances and peak amplitudes. Furthermore, σRR and σQRS metrics were added to quantify RR distances regularity and QRS durations, respectively. Regular grammar with the addition of some requirements and deterministic automata proved functional for both biomedical signals and ECG signal diagnosis. The suggested method provided a sensitivity rate of 99.74% and the positive predictivity rate of 99.86%. The algorithm was compared to other works in the literature and the quality performance detection was compared with several algorithms tested and validated on the MIT-BIH database. A head-to-head comparison in terms of sensitivity and CPU runtime was provided with the wavelet method.

Three-dimensional interpolation methods to spatiotemporal EEG mapping during various behavioral states

This work applies a novel method called multiquadratic interpolation that represents a 3D brain activity following a spatiotemporal mode. It also develops other classical interpolation techniques (barycentric, spline), which are based on the calculation of the Euclidean distance between the estimated and measured electrodes. Then, it modifies these methods by substituting the Euclidean distance by the corresponding arc length. Starting from 19 real electrodes for generating the electroencephalogram (EEG) potential representations of healthy subjects having three different behavioral brain states, a 3D EEG mapping of 128 electrodes was obtained. The proposed multiquadratic interpolation is evaluated by comparing it with the other methods by calculating the root mean squared error and processing time means.

Local deformation analysis of the heart left ventricle using SPHARM descriptors and modified hotelling T2 metric

A closed surface of a 3D object with spherical topology can be expressed into a series of spherical harmonic (SPHARM) functions. The SPHARM descriptors allow accurate representation of large data sets with small number of coefficients. In this paper, we present a new approach for regional deformation analysis of the heart left ventricle (LV). We use spherical harmonics (SPHARM) shape descriptors with the modified Hotelling T2 metric in order to characterize the myocardium disease extent and its severity. This approach has been validated with real data obtained from myocardial scintigraphy imaging techniques. The obtained results show its effectiveness and validity.

Scintigraphic image segmentation based on grammatical inference and spiral matrix

This paper deals with an image segmentation tool inspired from grammar formalism and based on spiral matrix. We are to set a scintigraphic image as a set of lexemes based on a vocabulary of intensities and a set of grammatical rules. Thus, the endocardium, epicardium and epicardial muscle edges are detected. In addition, a set of quantitative information is also deduced such as endocardium area, endocardium diameter and epicardial muscle thickness. This type of task is intended for medical diagnosis assistance. To validate our method, we have segmented a set of real scintigraphic images.

Novel Technique for Image Segmentation Based on Grammar Parsing and Hilbert Transform

The goal of parsing is to determine whether or not one word belongs to one specified language generated by a grammar. Therefore, the present paper is aimed at exploiting grammar formalism in image processing, especially segmentation. For the English language, the words are those that I am trying to write whereas for an image, the words are the edges and homogeneous regions. We managed to define an image as a set of letters based on image vocabulary, grammar formalism and Hilbert transform for region description. One region is considered as a word recognized by an automaton. We will demonstrate how grammar parsing is practical for synthetic and real images. Indeed, this task is of great help in real time images and video processing with the possibility of taking care of runtime and accuracy challenges.