RESUMO
Awake Surgery (AS) is considered the best treatment for brain tumors located in or near eloquent areas. During this intervention, Direct Electrical Stimulations (DES) are delivered by the surgeon on the patient's brain in order to obtain an accurate brain mapping of the patient. The patient is asked to perform various tasks (e.g. counting, object naming, emotion recognition) through neuropsychological tests during these stimulations. These DES may cause a reversible lesion inducing deficits on the patient which can be observed during these tasks by the medical staff. The resection is then performed or not according to the patient's response. The intraoperative deficits can take several forms and can be difficult to analyze and identify. The development of new solutions allowing the automatic detection of these deficits could be therefore essential. However, still today, no structured and organized AS dedicated database is available that could be used to train and test these algorithms. We propose a modular system allowing the synchronized multimodal acquisition of various information including physiological measurements, DES signals and parameters, and task-related data to create such database.Clinical relevance- Acquiring synchronized multimodal data during AS will allow the creation of a dedicated database that could then be used to reveal new correlations between DES and the patient's response, and to develop and test new algorithms for the automatic detection of deficits.