Hervé H Rix

Assuming two positive overlapping signals, with known shapes, the proposed method estimates the distances between their mean positions, width and area ratios. The data are two profiles representing the component shapes: no parametric model is assumed. The algorithm seeks shape equality between a linear combination of observation and first component, and the second component, in function of the area ratio. At the minimum shape difference the three parameters (distance between components, scaling factor and area ratio) are estimated. After theory, simulations are presented on Gaussian signals. Then, the method was applied on ECG signals from BSPM device during exercise on healthy people. The aim is mainly to get time distance between each T-wave and the P-wave of the following beat, on a given lead, in case of overlapping. Shape and width of the T-wave were shown to be constant before P-wave interference, which allowed taking such a real T-wave as first component model. Assumption of the same shape for the second component gave good results, as can be viewed on the reconstructed signals.

Inaccurate electrode placement and differences in inter-individual human anatomies can lead to misinterpretation of ECG examination. The aim of the study was to investigate the effect of precordial electrodes displacement on morphology of the ECG signal in a group of 60 patients with diagnosed cardiac disease. Shapes of ECG signals recorded from precordial leads were compared with signals interpolated at the points located at a distance up to 5 cm from lead location. Shape differences of the QRS and ST-T-U complexes were quantified using the distribution function method, correlation coefficient, root-mean-square error (RMSE), and normalized RMSE. The relative variability (RV) index was calculated to quantify inter-individual variability. ECG morphology changes were prominent in all shape parameters beyond 2 cm distance to precordial leads. Lead V2 was the most sensitive to displacement errors, followed by leads V3, V1, and V4, for which the direction of electrodes displacement plays a key role. No visible changes in ECG morphology were observed in leads V5 and V6, only scaling effect of signal amplitude. The RV ranged from 0.639 to 0.989. Distortions in ECG tracings increase with the distance from precordial lead, which are specific to chosen electrode, direction of displacement, and for ECG segment selected for calculations.

In this paper, we propose a method for detecting alterations in the Ensemble Spontaneous Activity (ESA), a random signal representing the composite spontaneous contribution of the auditory nerve recorded on the round window. The proposed method is based on shape analysis of the ESA amplitude histogram. For this task, we use a recent approach, the Corrected Integral Shape Averaging (CISA). Using this approach, a shape clustering algorithm is proposed to classify healthy and pathological ESA signals generated by a recent ESA model. This model allows a precise simulation of neural mechanisms occurring in the auditory nerve. The obtained results demonstrate that this shape analysis is very sensitive for detecting a small number of fibers with correlated firing, supposed to occur during a particular type of tinnitus. In comparison, the classical spectral index fails in this detection.

The authors study the asymptotic error variance of the ARMA (autoregressive moving-average) parameters. The ARMA estimation method involves a two-step procedure: first, the AR parameters are estimated using the Burg algorithm and the time-varying components of a Kalman filter gain. Then the MA parameters are obtained using a fast identification algorithm derived from Chandrasekhar equations. The authors report on results