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Classification in Postural Style Based on Stochastic Process Modeling

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  • Denis Christophe

    (Université Paris-Est Marne-la-Vallée, France)

Abstract

We address the statistical challenge of classifying subjects as hemiplegic, vestibular or normal based on complex trajectories obtained through two experimental protocols designed to evaluate potential deficits in postural control. The classification procedure involves a dimension reduction step where the complex trajectories are summarized by finite-dimensional summary measures based on a stochastic process model for a real-valued trajectory. This allows us to retrieve from the trajectories information relative to their temporal dynamic. A leave-one-out evaluation yields a 79% performance of correct classification for a total of n=70$$n = 70$$ subjects, with 22 hemiplegic (31%), 16 vestibular (23%) and 32 normal (46%) subjects.

Suggested Citation

  • Denis Christophe, 2014. "Classification in Postural Style Based on Stochastic Process Modeling," The International Journal of Biostatistics, De Gruyter, vol. 10(2), pages 251-260, November.
    • Handle: RePEc:bpj:ijbist:v:10:y:2014:i:2:p:10:n:1
    DOI: 10.1515/ijb-2012-0017
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    References listed on IDEAS

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    1. Gareth M. James & Trevor J. Hastie, 2001. "Functional linear discriminant analysis for irregularly sampled curves," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(3), pages 533-550.
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