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.

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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.I.

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