Improvements of scale fourier linear combiner for impedance cardiography analysis.

In this paper, we present two additions to the SFLC algorithm in order to improve the beat by beat estimation of fiducial points (B and X) and the maximum value of the derivative in impedance cardiography signal: addition of a reference input and scanning each beat more than once. On data synthesized from real ICG which exhibits beat by beat changes and baseline variations, we used statistical measures to show that the modified algorithms give accurate beat by beat estimation conversely to the original version of SFLC. We also give results on a real ICG using phono cardiography as a reference. In this case too, results show the pertinence of the proposed improvements.

Impedance cardiography filtering using scale Fourier linear combiner based on RLS algorithm.

The Cardiac Output (CO) can be calculated from the thoracic cardio-impedance signal from several methods, and all of them are linked to the frequency information, information that is limited by the type of filtering used before. A methodology is proposed to evaluate the effect of the commonly used methods of filtering, and an improvement of the SFLC LMS-based algorithm by the use of RLS algorithm is also tested. Performances of algorithms are then evaluated considering different types of noise such as white noise or combination of sinusoidal noises to simulate the effect of respiration and body movements.

Parameter estimation and order selection for an empirical model of VO2 on-kinetics.

In humans, VO2 on-kinetics are noisy numerical signals that reflect the pulmonary oxygen exchange kinetics at the onset of exercise. They are empirically modelled as a sum of an offset and delayed exponentials. The number of delayed exponentials; i.e. the order of the model, is commonly supposed to be 1 for low-intensity exercises and 2 for high-intensity exercises. As no ground truth has ever been provided to validate these postulates, physiologists still need statistical methods to verify their hypothesis about the number of exponentials of the VO2 on-kinetics especially in the case of high-intensity exercises. Our objectives are first to develop accurate methods for estimating the parameters of the model at a fixed order, and then, to propose statistical tests for selecting the appropriate order. In this paper, we provide, on simulated Data, performances of Simulated Annealing for estimating model parameters and performances of Information Criteria for selecting the order. These simulated Data are generated with both single-exponential and double-exponential models, and noised by white and Gaussian noise. The performances are given at various Signal to Noise Ratio (SNR). Considering parameter estimation, results show that the confidences of estimated parameters are improved by increasing the SNR of the response to be fitted. Considering model selection, results show that Information Criteria are adapted statistical criteria to select the number of exponentials.