Authors:
Xavier Sánchez Corrales
1
;
2
;
Jordi Solé-Casals
3
;
2
;
Enrique Arroyo García
4
and
Diego Palao Vidal
4
Affiliations:
1
Researcher, Mental Health Department, Consorci Corporació Sanitària Parc Taulí, Sabadell, Barcelona, Spain
;
2
Data and Signal Processing Research Group, University of Vic–Central University of Catalonia, Vic, Spain
;
3
Department of Psychiatry, University of Cambridge, Cambridge, U.K.
;
4
Consorci Corporació Sanitària Parc Taulí, Sabadell, Barcelona, Spain
Keyword(s):
Depression, IMF (Intrinsic Mode Functions), EMD (Empirical Mode Decomposition), Bootstrapping, Gaussian Kernel.
Abstract:
This study investigates the differences in male voice between healthy individuals and individuals with depression, using Empirical Mode Decomposition (EMD) analysis. Voice recordings from 25 men with depression and 76 without were analyzed. The methodology consisted of extracting 16 Intrinsic Mode Functions (IMFs) from 20-second voice segments, followed by statistical analyses including bootstrapping of means and standard deviations with False Discovery Rate (FDR) correction, comparison of probability density functions, and the application of a Gaussian kernel. The results showed significant differences between the means and standard deviations, The application of the Gaussian kernel revealed more pronounced differences in IMFs 2 to 6, providing more specific discrimination than traditional statistical methods. The study contributes to the development of non-invasive and objective diagnostic tools for depression.