Multivariate predictive model for dyslexia diagnosis.

Dyslexia is a specific disorder of language development that mainly affects reading. Etiological researches have led to multiple hypotheses which induced various diagnosis methods and rehabilitation treatments so that many different tests are used by practitioners to identify dyslexia symptoms. Our purpose is to determine a subset of the most efficient ones by integrating them into a multivariate predictive model.

Smart multisensor kernel.

We describe in this paper a smart multisensor kernel, given the shape of a wriststrap and able to characterise a current physiological state among a number of ones resulting from a previous analysis, and to transmit those results using a radio link. The main advantage of this product is its adaptability. As examples, we describe two applications which are the remote monitoring of elderly people and the sleep staging.