Local Assessment of Statokinesigram Dynamics in Time: An in-Depth Look at the Scoring Algorithm
Ioannis Bargiotas, Julien Audiffren, Nicolas Vayatis, Pierre-Paul Vidal, Alain P. Yelnik, Damien Ricard
→ BibTeX
@article{ipol.2019.251,
    title   = {{Local Assessment of Statokinesigram Dynamics in Time: An in-Depth Look at the Scoring Algorithm}},
    author  = {Bargiotas, Ioannis and Audiffren, Julien and Vayatis, Nicolas and Vidal, Pierre-Paul and Yelnik, Alain P. and Ricard, Damien},
    journal = {{Image Processing On Line}},
    volume  = {9},
    pages   = {143--157},
    year    = {2019},
    doi     = {10.5201/ipol.2019.251},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2019.251}}
published
2019-06-11
reference
Ioannis Bargiotas, Julien Audiffren, Nicolas Vayatis, Pierre-Paul Vidal, Alain P. Yelnik, and Damien Ricard, Local Assessment of Statokinesigram Dynamics in Time: An in-Depth Look at the Scoring Algorithm, Image Processing On Line, 9 (2019), pp. 143–157. https://doi.org/10.5201/ipol.2019.251

Communicated by Laurent Oudre
Demo edited by Julien Audiffren

Abstract

In this work we discuss the multidimensional scoring approach proposed by Bargiotas and al. [I. Bargiotas, J. Audiffren, N. Vayatis, P-P. Vidal, S. Buffat, A.P. Yelnik and Damien Ricard, On the importance of local dynamics in statokinesigram: a multivariate approach for postural control evaluation in elderly, PloS one, 13 (2018)] which locally characterizes statokinesigrams - the trajectory of the center of pressure, which is highly correlated with static balance quality - on small time intervals, or blocks. This approach highlights the local dynamics of the trajectories, and we show that the resulting characterization can be used to provide a global score in order to evaluate the postural control. We evaluate our approach using the statokinesigram of 126 community-dwelling elderly, and show that it provides an efficient tool to discriminate between fallers and non-fallers.

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