Design of a Multimodal Database for Research on Automatic Detection of Severe Apnoea Cases

The aim of this paper is to present the design of a multimodal database suitable for research on new possibilities for automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases can be very useful to give priority to their early treatment optimizing the expensive and time-consuming tests of current diagnosis methods based on full overnight sleep in a hospital. This work is part of an on-going collaborative project between medical and signal processing groups towards the design of a multimodal database as an innovative resource to promote new research efforts on automatic OSA diagnosis through speech and image processing technologies. In this contribution we present the multimodal design criteria derived from the analysis of specific voice properties related to OSA physiological effects as well as from the morphological facial characteristics in apnoea patients. Details on the database structure and data collection methodology are...

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Rubén Fernández Pozo, Luis A. Hernández Gómez, Eduardo López, José Alcazar, Guillermo Portillo, Doroteo Torre Toledano
• Keywords: Automatic Osa, Education, LREC 2008, Multimodal Database, OSA Multimodal Database