Évaluation du signal EEG intra-auriculaire pour le suivi long terme des patients

Electroencephalography (EEG) is a non-invasive technique that records the brain's electrical activity, providing a window into the dynamic functioning of the central nervous system. In 1924, Hans Berger, became the first to measure human brain waves, marking a pivotal moment in the history of clinical EEG use (Berger, 1929). Since then, EEG has become a gold standard of neurological diagnostics, enabling the real-time recording of electrical fluctuations in the brain through electrodes placed on the scalp. EEG's importance lies in its ability to quickly and accurately detect abnormalities in brain activity, which is particularly valuable in diagnosing and monitoring neurological conditions such as epilepsy and sleep disorders. In the context of epilepsy, EEG is a critical tool for identifying the brain regions where seizures originate. Even in the absence of overt clinical seizures, epileptiform abnormalities—characterized by distinctive spikes and slow waves—can be detected, providing essential clues for diagnosis (Fisher et al., 2005). These abnormalities manifest as sudden, brief, and stereotypical waveforms that differ from the normal background activity, indicating the potential presence of epileptic foci (Fisch, B. J., 2012). Similarly, EEG plays a central role in the diagnosis and management of sleep disorders. In polysomnography, a comprehensive sleep study, EEG is combined with other physiological measures such as eye movements (EOG), muscle activity (EMG), heart rate (ECG), and respiratory effort to assess sleep architecture and disturbances. This multidimensional approach allows clinicians to diagnose conditions such as sleep apnea. EEG is crucial for analyzing sleep cycles, particularly by distinguishing between the different stages of sleep—rapid eye movement (REM) and non-rapid eye movement (NREM). Deviations from normal patterns in these stages can indicate underlying sleep disorders, providing vital information for determining the appropriate intervention. This PhD project builds upon the well-established role of EEG in clinical and research settings by advancing the development of an in-ear EEG device aimed at improving patient care through long-term monitoring. Traditional scalp EEG, while effective, can be cumbersome for long-term use due to its setup complexity and the discomfort associated with wearing multiple electrodes. The in-ear EEG device aims to provide a more comfortable and practical alternative, especially for patients suffering from chronic conditions like epilepsy and sleep disorders. This wearable technology would allow for continuous monitoring over extended periods and in non-clinical settings, such as the home, enabling a more accurate and comprehensive assessment of a patient's neurological state. This shift toward long-term, real-world monitoring could revolutionize the diagnosis and treatment of neurological conditions, allowing clinicians to detect subtle changes in brain activity that might be missed during short clinical visits. Our research has yielded promising results, with encouraging similarities observed between the signals recorded by the in-ear device and traditional scalp EEG, particularly in the temporal regions (T7-T8 derivations). These findings suggest that in-ear EEG technology has the potential to provide signal quality comparable to that of conventional systems, making it a viable option for real-world clinical applications. However, challenges remain, particularly in terms of refining the device's design, improving the materials used, and optimizing signal processing techniques to reduce artifacts. Further research and development are needed to address these issues, but the progress made so far demonstrates the significant potential of in-ear EEG devices to transform the field of neurological monitoring.