Mathematical modelling of sleep fragmentation diagnosis

Autor: Emna Bouazizi, Marie-Françoise Mateo, Jacques Grapperon, Iuliana Cartacuzencu, Antoine Elias, Rabih A. L. I. Ahmad, Jean-Marc Ginoux, D. D’Amore, Olivier Tible, Jean-Philippe Suppini, Roomila Naeck, Adriana Raspopa
Přispěvatelé: Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA), Unité de Recherche Clinique du CHITS, Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Intercommunal Toulon la Seyne sur mer, Sommeil, Addiction et Neuropsychiatrie [Bordeaux] (SANPSY), Université de Bordeaux (UB)-CHU de Bordeaux Pellegrin [Bordeaux]-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU), Sommeil, Attention et Neuropsychiatrie [Bordeaux] (SANPSY), Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU)
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: Biomedical Signal Processing and Control
Biomedical Signal Processing and Control, 2016, 24, pp.83-92. ⟨10.1016/j.bspc.2015.10.001⟩
Biomedical Signal Processing and Control, Elsevier, 2016, 24, pp.83-92. ⟨10.1016/j.bspc.2015.10.001⟩
ISSN: 1746-8094
DOI: 10.1016/j.bspc.2015.10.001⟩
Popis: International audience; Polysomnography (PSG) is the recording during sleep of multiple physiological parameters enabling to diagnose sleep disorders and to characterize sleep fragmentation. From PSG several sleep characteristics such as the micro arousal rate (MAR), the number of sleep stages shifts (SSS) and the rate of intra sleep awakenings (ISA) can be deduced each having its own fragmentation threshold value and each being more or less important (weight) in the clinician's diagnosis according to his specialization (pulmonologist, neurophysiologist and technical expert). In this work we propose a mathematical model of sleep fragmentation diagnosis based on these three main sleep characteristics (MAR, SSS, ISA) each having its own threshold and weight values for each clinician. Then, a database of 111 PSG consisting of 55 healthy adults and 56 adult patients with a suspicion of obstructive sleep apnoea syndrome (OSAS), has been diagnosed by nine clinicians divided into three groups (three pulmonologists, three neurophysiologists and three technical experts) representing a panel of polysomnography experts usually working in a hospital. This has enabled to determine statistically the thresholds and weights values which characterize each clinician's diagnosis. Thus, we show that the agreement between each clinician's diagnosis and each corresponding mathematical model goes from substantial (κ > 61%) to almost perfect (κ > 81%), according to their specialization and so, that the mean value of the agreements of each group is also substantial (κ > 73%) despite the existing variability between clinicians. It follows from this result that our mathematical model of sleep fragmentation diagnosis is a posteriori validated for each clinician.
Databáze: OpenAIRE
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