Feature selection for spontaneous speech analysis to aid in Alzheimer's disease diagnosis: A fractal dimension approach

Feature selection for spontaneous speech analysis to aid in Alzheimer’s disease diagnosis: A fractal dimension approach Karmele López-de-Ipiña a,∗, Jordi Solé-Casals b, Harkaitz Eguiraun c, J.B. Alonso d, C.M. Travieso d, Aitzol Ezeiza a, Nora Barroso a, Miriam Ecay-Torres e, Pablo Martinez-Lage e, Blanca Beitia f a Department of Systems Engineering and Automation, University of the Basque Country, Donostia, Spain b Data and Signal Processing Research Group, University of Vic – Central University of Catalonia, Vic, Spain c Research Center for Experimental Marine Biology and Biotechnology, Plentzia Marine Station, University of the Basque Country, UPV/EHU, Plentzia, Bizkaia, Spain d Signal and Communications Department, The Institute for Technological Development and Innovation on Communications, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain e Neurology Department CITA-Alzheimer Foundation, Donostia, Spain f Department of Mathematics, University of the Basque Country, Vitoria-Gasteiz, Spain