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Machine Learning techniques applied to eye movement analysis for early screening of learning disorders in young children

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Academic year: 2022

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Machine Learning techniques applied to eye movement analysis for early screening of learning disorders in young children

Principal investigators: Zoï Kapoula & Vivien Sainte Fare Garnot (Neurosciences), FRE 2022, CNRS Université de Paris Co-investigator: Ioana Ileana (Computer Science), Université de Paris

There is a longstanding controversy about the existence of eye movement disorders and their role in dyslexia and school learning disorders. Using REMOBI&AIDEAL innovations (https://orasis-ear.com) the CNRS IRIS Laboratory headed by Zoï Kapoula conducted a critical study in dyslexic and non-dyslexic teenagers. The study confirms intrinsic eye movement disorders particularly of their binocular coordination in dyslexia while testing with the REMOBI embedded device i.e. not related to reading (see Ward & Kapoula, Scientific Reports, Nature, 2020.

The present proposal concerns a large scale study at nursery and primary school children (5 to 7 years old). Binocular eye movements will be collected and analyzed to assess and treat preventively eye movement irregularities.

Intern's mission (trained in IA/Data Science & cloud services)

The intern will work on: structuring the database and optimizing the dataflow, conceiving and applying data noise reduction strategies, biomarker extraction using, and the application of various Machine Learing. Such techniques will be applied to the end of classifying children according to their binocular motor skills into four categories: normal development, inefficient development, disturbed development, and deficit. Both supervised and unsupervised Machine Learning techniques will be investigated, Classification algorithms will further be analyzed in order to evaluate their statistical and physiological relevance and reliability.

Pluridisciplinary cooperative aspects

The cooperation between the IRIS lab, expert in neurosciences of binocular motor control cognition and attention, and the LIPADE (which co-investigator Ioana Ileana is a member of), provides a unique opportunity to link the two research fields: Computer and Data Science and Neuroscience; it will provide a stimulating context for the student to get trained in a field that has Computer Science theoretical, educational and health significance. Noteworthy such approach in the field of Neuroscience is novel. Data obtained from humans and especially from young children are of high complexity and very difficult to be handled by classic statistics methods alone

Position available immediately. Send CV to zoi.kapoula@gmail.com, and ioana.ileana@gmail.com

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