Résumé
The basic theory of Higher Order Spectral Analysis and the most generally used Bispectrum are introduced in the paper. By certain experiments of EEG signal acquisition and bispectrum analysis, it is showed that the Higher Order Spectrum has an advantage over power spectrum, which is based on Second Order Statistics, in processing non-linear signal and restraining Gauss noise signal.
Sujets)
Électroencéphalographie , Méthodes , Traitement du signal assisté par ordinateurRésumé
On account of different thickness of tissues absorbing different doses of X ray, it is difficult to display anatomical details of different tissues on a single screen of DR equipment. In order to resolve this problem, the self-adaptive reverse S mode transformation algorithm is presented in the paper, which can modify darker regions and brighter regions respectively, and improve the visibility of weakly details.
Sujets)
Algorithmes , Amélioration d'image radiographique , MéthodesRésumé
Many researches have proved that auditory evoked potentials (AEP) can indicate the depth of anesthesia in the clinical practice. This paper introduces two methods of extracting AEP: the moving time average (MTA) model and the autoregressive model with exogenous input (ARX). In our study we used both the MTA model and the ARX model to extract AEP and the results show that using the ARX model can get the results significantly faster than using the MTA model, and the ARX model is more suitable for the real-time monitoring of the anesthetic depth.
Sujets)
Humains , Anesthésie , Méthodes , Électroencéphalographie , Méthodes , Potentiels évoqués auditifs , Physiologie , Surveillance peropératoire , Méthodes , Traitement du signal assisté par ordinateurRésumé
At the present time, a kind of monitoring technology assuring highly effectual anesthesia is urgently required in the clinical practice. Electroencephalogram (EEG) assumes a dominant position in the current research of the depth detection of anesthesia. In this paper, the monitoring technique of the depth detection of anesthesia by bispectral index (BIS) is systematically showed. The bispectral index is a compound parameter which is composed of time domain, frequency domain, and high order spectral subparameters of the electroencephalograph. This nonlinear compound calculation method is worth research and is of great significance to the development of a new monitor of closed-loop control of anesthesia.