Software Engineer Speech Brain- Computer Interface
Il y a 2 mois
Grenoble (38)
Position Duties
Projet : Environ 18,5 millions de personnes souffrent d'un trouble de la parole ou du langage dans le monde, et environ 300 000 en France. Plusieurs millions de ces situations font suite à des maladies neurodégénératives (telles que la sclérose latérale amyotrophique - SLA) ou à des accidents vasculaires sous-corticaux qui endommagent les voies motrices dédiées à l'articulation et à la phonation. Ces déficiences peuvent déboucher sur un syndrome d'enfermement (ou locked-In Syndrome - LIS) dans lequel les personnes sont incapables de parler alors que leurs capacités cognitives restent intactes. Dans ce contexte, les interfaces cerveau-ordinateur (BCI) visent à fournir à ces personnes des solutions de communication en enregistrant leurs signaux cérébraux et en les "traduisant" en parole artificielle produite par un synthétiseur [1]-[7]. Nos recherches se concentrent sur le développement d'un système BCI entièrement implantable qui reconstruit la parole à partir des signaux corticaux en temps réel.
Additional Information
Localisation : L'Institut des Neurosciences de Grenoble est une unité mixte de recherche de l'Institut National pour la Santé et la Recherche Médicale (INSERM) et de l'Université Grenoble Alpes. Le laboratoire collabore étroitement avec l'institut CEA-Clinatec pour mettre en place un essai clinique BCI parole chronique dédié aux personnes LIS.
Références bibliographiques:
[1] F. Bocquelet, T. Hueber, L. Girin, S. Chabardes, and B. Yvert, "Key considerations in designing a speech brain-computer interface," J. Physiol. Paris, vol. 110, no. 4, pp. 392-401, 2016.
[2] F. Bocquelet, T. Hueber, L. Girin, C. Savariaux, and B. Yvert, "Real-Time Control of an Articulatory-Based Speech Synthesizer for Brain Computer Interfaces," PLOS Comput. Biol., vol. 12, no. 11, p. e1005119, Nov. 2016.
[3] P. Roussel et al., "Observation and assessment of acoustic contamination of electrophysiological brain signals during speech production and sound perception," J. Neural Eng., vol. 17, p. 056028, 2020.
[4] D. A. Moses et al., "Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria," N. Engl. J. Med., vol. 385, no. 3, pp. 217-227, 2021.
[5] S. L. Metzger et al., "A high-performance neuroprosthesis for speech decoding and avatar control.," Nature, 2023.
[6] F. Willett et al., "A high-performance speech neuroprosthesis.," Nature, vol. 620, pp. 1031-36, 2023.
[7] G. Le Godais et al., "Overt speech decoding from cortical activity : a comparison of different linear methods," Front. Hum. Neurosci., vol. 17, no. June, p. 1124065, 2023.
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