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Understanding Parent-Infant Behaviors Using Non-negative Matrix Factorization

  • Ammar Mahdhaoui
  • Mohamed Chetouani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6456)

Abstract

There are considerable differences among infants in the quality of interaction with their parents. These differences depend especially on the infants development which affects the parent behaviors. In our study we are interested on 3 groups of infants: typical development infants (TD), autistic infants (AD) and mental retardation infants (MR). In order to identify the groups of signs/behaviors that differentiate the development of the three groups of children we investigated a clustering method NMF (non-negative matrix factorization), an algorithm based on decomposition by parts that can reduce the dimension of interaction signs to a few number of interaction behaviors groups. Coupled with a statistical data representation tf-idf, usually used for document clustering and adapted to our work, NMF provides an efficient method for identification of distinct interaction groups. Forty-two infants and their parents were observed in this study. Parent-infant interactions were videotaped by one of the parents at home during the first two years age of child.

Keywords

Parent-infant interaction Clustering tf-idf NMF Autism 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ammar Mahdhaoui
    • 1
  • Mohamed Chetouani
    • 1
  1. 1.Institut des Systèmes Intelligents et de Robotique, CNRS, UMR 7222Université Pierre & Marie CurieParisFrance

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