Title :
EOG segmentation using fast algorithms
Author :
Buzenac, V. ; Settineri, R. ; Najim, M. ; Paty, J.
Author_Institution :
Equipe Signal et Image de l´´ENSERB, Univ. de Bordeaux I, Talence, France
Abstract :
A new method is presented for segmentation of rapidly time-varying signals based on fast least squares algorithms, due to their low complexity. The detection test used is based on the likelihood variable which appears explicitly in the fast algorithms. In order to show the performances of the method, it is applied to E.O.G. (electrooculograms) signals
Keywords :
electroencephalography; least squares approximations; medical signal processing; EOG segmentation; EOG signals; detection test; electrooculograms; least squares algorithms; likelihood variable; rapidly time-varying signals; Autocorrelation; Electrooculography; Error correction; Image segmentation; Kalman filters; Least squares methods; Nonlinear filters; Resonance light scattering; Testing; Transversal filters;
Conference_Titel :
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1281-3
DOI :
10.1109/ISCAS.1993.393850
