Personalized sleep staging system using evolutionary algorithm and symbolic fusion.

This paper presents a novel system for automatic sleep staging based on evolutionary technique and symbolic intelligence. Proposed system mimics decision making process of clinical sleep staging using Symbolic Fusion and considers personal singularity with an adaptive thresholds setting up system using Evolutionary Algorithm. It proved to be an effective and promising system in personalizing sleep staging.

Decision System Integrating Preferences to Support Sleep Staging.

Scoring sleep stages can be considered as a classification problem. Once the whole recording segmented into 30-seconds epochs, features, extracted from raw signals, are typically injected into machine learning algorithms in order to build a model able to assign a sleep stage, trying to mimic what experts have done on the training set. Such approaches ignore the advances in sleep medicine, in which guidelines have been published by the AASM, providing definitions and rules that should be followed to score sleep stages.

Towards a Wireless Smart Polysomnograph Using Symbolic Fusion.

Polysomnography is the gold standard test for sleep disorders among which the Sleep Apnea Syndrome (SAS) is considered a public health issue because of the increase of the cardio-and cerebro-vascular risk it is associated with. However, the reliability of this test is questioned since sleep scoring is a time-consuming task performed by medical experts with a high inter- and intra-scorers variability, and because data are collected from 15 sensors distributed over a patient's body surface area, using a wired connection which may be a source of artefacts for the patient's sleep. We have used symbolic fusion to support the automated diagnosis of SAS on the basis of the international guidelines of the AASM for the scoring of sleep events.

Dynamical and Mechanistic Reconstructive Approaches of T Lymphocyte Dynamics: Using Visual Modeling Languages to Bridge the Gap between Immunologists, Theoreticians, and Programmers.

Dynamic modeling of lymphocyte behavior has primarily been based on populations based differential equations or on cellular agents moving in space and interacting each other. The final steps of this modeling effort are expressed in a code written in a programing language. On account of the complete lack of standardization of the different steps to proceed, we have to deplore poor communication and sharing between experimentalists, theoreticians and programmers.

Evaluating OPTISAS, a visual method to analyse sleep apnea syndromes.

The sleep apnea syndrome is a real public health problem. Improving its diagnosis using the polysomnography is of huge importance. Optisas was a visual method allowing translating the polysomnographic data into a meaningful image.

OPTISAS a new method to analyse patients with Sleep Apnea Syndrome.

OPTISAS is a visualization method that allows describing very precisely a patient with Sleep Apnea Syndrome. Using the events scored by the physician, our method gives a set of graphs that are a detailed representation of the condition, sleep stage and position, in which the events occur. This helps for the diagnosis.