OBJECTIVES: The aim of this research has been to introduce an automatic method, simple from the mathematical and computational points of view, for the recognition and classification of the A-phases of the cyclic alternating pattern. METHODS: The automatic method was based on the computation of 5 descriptors, which were derived from the EEG signal and were able to provide a meaningful data reduction. Each of them corresponded to a different frequency band. RESULTS: The computation of these descriptors, followed by the introduction of two suitable thresholds and of simple criteria for logical discrimination, provided results which were in good agreement with those obtained with visual analysis. The method was versatile and could be applied to the study of other important microstructure phenomena by means of very small adaptations. CONCLUSIONS: The simplicity of the method leads to a better understanding and a more precise definition of the visual criteria for the recognition and classification of the microstructure phenomena.
OBJECTIVES: The aim of this research has been to introduce an automatic method, simple from the mathematical and computational points of view, for the recognition and classification of the A-phases of the cyclic alternating pattern. METHODS: The automatic method was based on the computation of 5 descriptors, which were derived from the EEG signal and were able to provide a meaningful data reduction. Each of them corresponded to a different frequency band. RESULTS: The computation of these descriptors, followed by the introduction of two suitable thresholds and of simple criteria for logical discrimination, provided results which were in good agreement with those obtained with visual analysis. The method was versatile and could be applied to the study of other important microstructure phenomena by means of very small adaptations. CONCLUSIONS: The simplicity of the method leads to a better understanding and a more precise definition of the visual criteria for the recognition and classification of the microstructure phenomena.
Authors: Sara Mariani; Elena Manfredini; Valentina Rosso; Andrea Grassi; Martin O Mendez; Alfonso Alba; Matteo Matteucci; Liborio Parrino; Mario G Terzano; Sergio Cerutti; Anna M Bianchi Journal: Med Biol Eng Comput Date: 2012-03-20 Impact factor: 2.602
Authors: Martin Oswaldo Mendez; Ioanna Chouvarda; Alfonso Alba; Anna Maria Bianchi; Andrea Grassi; Edgar Arce-Santana; Guilia Milioli; Mario Giovanni Terzano; Liborio Parrino Journal: Med Biol Eng Comput Date: 2015-08-08 Impact factor: 2.602