PhD graduated
Team : SYEL
Departure date : 12/12/2016

Supervision : Patrick GARDA

Co-supervision : PINNA Andrea

An E-health System for Personalized Automatic Sleep Stages Classification

In this thesis, a personalized automatic sleep staging system is proposed by combining symbolic fusion and feedback system control technique. Symbolic fusion is inspired by the decision-making process of clinical sleep staging. It starts from the extraction of digital parameters from raw polysomnography signals and it goes up to a high-level symbolic interpretation through a features extraction process. At last, the decision is generated using rules inspired by international guidelines in sleep medicine. Meanwhile, the symbols and the features computations depend on a set of thresholds, whose determination is a key issue. In this thesis, two different FSC algorithms, Differential Evolution and Cross Entropy, were studied to compute these thresholds automatically.
Individual variability was often ignored in existing automatic sleep staging systems. However, an individual variability was observed in many aspects of sleep research (such as polysomnography recordings, sleep patterns, sleep architecture, sleep duration, sleep events, etc.). In order to improve the effectiveness of the sleep stages classifiers, a personalized automatic sleep staging system that can be adapted the different persons and take individual variability into consideration was explored and evaluated.
The perspectives of this work are based on evaluating the complexity and the performances of these algorithms in terms of latencies and hardware resource requirements, in order to target a personalized automated embedded sleep staging system.

Defence : 12/12/2016 - 10h - Site Jussieu 24-25/405

Jury members :

M. Kurosh MADANI, Professeur, Université Paris Est Créteil (UPEC), Rapporteur
M. Etienne SICARD, Professeur, Institut National des Sciences Appliquées de Toulouse (INSA), Rapporteur
M. Jérôme BOUDY, Professeur, Télécom SudParis
M. Christophe MARSALA, Professeur, Université Pierre et Marie Curie (UPMC)
Mme. Marie-Christine JAULENT, Directrice de recherche, Institut national de la santé et de la recherche médicale (INSERM)

2015-2019 Publications