This work was supported in part by the FCT - Foundation for Science and Technology, in part by the I.P./MCTES through national funds (PIDDAC), within the scope of CISUC R&D Unit under Projects UIDB/00326/2020 and UIDP/00326/2020, in part by the Ph.D. scholarships under Projects SFRH/BD/135686/2018 and DFA/BD/4927/2020, in part by the WELMO, in part by the Horizon 2020 Framework Programme of the European Union under Grant 825572, in part by the FCT project Lung@ICU under Grant DSAIPA/AI/0113/2020, in part by the Fundo Europeu de Desenvolvimento Regional (FEDER), in part by the Programa Operacional Competitividade e Internacionalização (COMPETE), in part by the iBiMED under Project POCI- 01-0145-FEDER-007628, and in part by the FCT under Project UIDB/04501/2020.

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This work was supported in part by the FCT - Foundation for Science and Technology, in part by the I.P./MCTES through national funds (PIDDAC), within the scope of CISUC R&D Unit under Projects UIDB/00326/2020 and UIDP/00326/2020, in part by the Ph.D. scholarships under Projects SFRH/BD/135686/2018 and DFA/BD/4927/2020, in part by the WELMO, in part by the Horizon 2020 Framework Programme of the European Union under Grant 825572, in part by the FCT project Lung@ICU under Grant DSAIPA/AI/0113/2020, in part by the Fundo Europeu de Desenvolvimento Regional (FEDER), in part by the Programa Operacional Competitividade e Internacionalização (COMPETE), in part by the iBiMED under Project POCI- 01-0145-FEDER-007628, and in part by the FCT under Project UIDB/04501/2020.

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123-Feb-2023Automatic wheeze segmentation using harmonic-percussive source separation and empirical mode decompositionRocha, Bruno M. ; Pessoa, Diogo ; Marques, Alda; Carvalho, Paulo de ; Paiva, Rui Pedro articleopenAccess