Detection of Complex Fractionated Atrial Electrograms (CFAE)using Recurrence Quantification Analysis.

International audienceAtrial fibrillation (AF) is the most common cardiac arrhythmia but its proarrhythmic substrate remains unclear. Reentrant electrical activity in the atria may be responsible for AF maintenance. Over the last decade, different catheter ablation strategies targeting the electrical substrate of the left atrium have been developed in order to treat AF. Complex Fractionated Atrial Electrograms (CFAE) recorded in the atria may represent not only reentry mechanisms, but also a large variety of bystander electrical wave fronts. In order to identify CFAE involved in AF maintenance as a potential target for AF ablation, we have developed an algorithm based on nonlinear data analysis using Recurrence Quantification Analysis (RQA). RQA features make it possible to quantify hidden structures in a signal and offer clear representations of different CFAE types. Five RQA features were used to qualify CFAE areas previously tagged by a trained electrophysiologist. Data from these analyzes were used by two classifiers to detect CFAE periods in a signal. While a single feature is not sufficient to properly detect CFAE periods, the set of five RQA features combined with a classifier were highly reliable for CFAE detection

Reconstruction from experimental data of a mathematical model of cardiac tissue: A feasibility study

The aim of this work is to study the feasability of reconstruction mathematical model of cardiac tissue from intracellular recordings. It is studied using simulated data and the presented method is applied to the Aliev-Panfilov model. A dissociated scheme is proposed and the estimation of some parameters is investigated in case of ideal or noisy data. The influence of the number and distribution of electrodes is then studied. 1

Pattern image enhancement by automatic focus correction

International audienceOptical analysis techniques are key tools for the failure analysis and defect localization in integrated circuits. Using a confocal laser microscope, it is possible to extract different pieces of information such as spatial distribution of signals or voltage waveforms. Blur is getting a more and critical issue as technology pitch is getting smaller, very close to resolution limits. Find the correct focus, is a recurrent problem to solve in optical microscopy. The expert has to correct the blur disrupting the image, by manually searching the good focus. By consequences, this step may take a long time to identify regions of interest in the circuit. With this purpose in mind, the aim of this paper, is to propose an automatic process estimating the out-of-focus blur parameters characterized by specific attributes. Proposed technique takes advantage of extracted features in the Discrete Cosine Transform (DCT) of blurred images. The blur information is identified and allows to recover the blur's kernel. Finally, the accuracy and the robustness of the suggested process is demonstrated on real blurred images.Focus correctionFailure analysisDiscrete Cosine TransformThresholdingRadon transformImage processin

Unsupervised learning for signal mapping in dynamic photon emission

International audienceDynamic photon emission is an efficient tool for timing analysis of various areas. However, advances in transistors integration bring more complex test patterns and more objects to investigate. As a consequence, understanding the analyzed area and finding nodes of interest can be difficult. In this paper, a method for drawing synthesis of the various signals met inside an area is reported. It is based on unsupervised learning tool for dimension reduction and clustering. The process is applied to real data to show its efficiency and its quality is evaluated

Signal and image processing techniques for VLSI failure analysis

International audienc

Dynamics of a charge-controlled memristor in master–slave coupling

International audienceThe application of memristor in non-linear diffusive network is introduced. A charged-controlled memristor model is used in the quantitative study of pixel-to-pixel communication via a memristor. To quantitatively understand the behaviour of the system, the authors emphasised on two cells: master and slave. Information is launched from the master cell to the slave cell through a memristor and the dynamics, as well as, the saturation of the system is observed

Improvement of signal to noise ratio in electro optical probing technique by wavelets filtering

International audienceElectro Optical Probing (EOP) technique is an efficient backside contacless technique to measure waveforms in modern VLSI circuits. The signal related intensity variation of the reflected beam is very weak therefore, to acquire a signal with enough Signal to Noise Ratio, averaging techniques are usually performed. Resulting acquisition time for one waveform are too long to implement point to point probing to image mode. To overcome this limitation, we have developped a new filtering by wavelets approach to keep a good SNR while significantly reducing this acquisition time. It opens the doors to new multipoint probing applications. In this paper, we describe the technique, its efficiency in terms of SNR, execution time and limits