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Digital Methods for EEG-fNIRS BioMarkers of Bipolar Disorders

Technological challenge: Health and environment technologies, medical devices (learn more)

Department: Département Microtechnologies pour la Biologie et la Santé (LETI)

Laboratory: Laboratoire Systèmes Pour la Personne

Start Date: 01-10-2022

Location: Grenoble

CEA Code: SL-DRT-22-0594

Contact: anne.planat-chretien@cea.fr

Bipolar disorder is a chronic adult psychiatric condition affecting between 0.5 and 1% of the population, with many unmet medical needs in terms of treatment. One of the key issues is earlier diagnosis for a better management of the pathology. In this context, the Laboratory of Systems for the Person (LS2P) of CEA-LETI proposes to take up the crucial challenge of patient monitoring in ambulatory conditions or at home. The aim of the thesis is to address bipolar disorders for the first time by identifying new physiological and numerical bio-markers through the use of electroencephalography (EEG) and near-infrared functional spectroscopy (fNIRS) - two modalities that can be potentially integrated into a wearable medical device (DM). These two modalities provide complementary information, respectively the electrical activity and the cortical hemodynamic response. The patient database is acquired through synchronized commercial EEG and fNIRS systems in collaboration with two international reference clinical centers, the Grenoble University Hospital and NeuroSpin in Saclay. The numerical methods developed during the thesis allow to cross a methodical gap in the real-time multiparametric analysis of the data - addressing at the same time data pre-processing, extraction of spatio-temporal and/or frequential features, multimodal data fusion, intra-patient or inter-patient data registration, and classification. At the end of this work, the PhD student should be able to define new EEG-fNIRS Bio-markers, the localization of targeted areas and the connectivity between these regions, the specifications of a wearable system for bipolar disorders and its associated analysis method. The development of the DM will be part of a specific project after the thesis. The PhD student has a background in Signal Processing and Biomedical Engineering.

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