Chaotic Properties of Gait Kinematic Data

Michal Piorek
Abstract : Time delay reconstruction for real systems is a widely explored area of nonlinear time series analysis. However, the majority of related work relates only to univariate time series, while multivariate time series data are common too. One such example is human gait kinematic data. The main goal of this article is to present a method of nonlinear analysis for kinematic time series. This nonlinear analysis is designed for detection of chaotic behavior. The presented approach also allows for the largest Lyapunov’s exponent estimation for kinematic time series. This factor helps in judging the stability of the examined system and its chaotic properties.
Type de document :
Communication dans un congrès
Khalid Saeed; Władysław Homenda. 14th Computer Information Systems and Industrial Management (CISIM), Sep 2015, Warsaw, Poland. Springer, Lecture Notes in Computer Science, LNCS-9339, pp.111-119, 2015, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-24369-6_9〉
Liste complète des métadonnées

https://hal.inria.fr/hal-01444509
Contributeur : Hal Ifip <>
Soumis le : mardi 24 janvier 2017 - 10:42:03
Dernière modification le : mercredi 25 janvier 2017 - 01:04:03
Document(s) archivé(s) le : mardi 25 avril 2017 - 18:12:51

Fichier

978-3-319-24369-6_9_Chapter.pd...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Michal Piorek. Chaotic Properties of Gait Kinematic Data. Khalid Saeed; Władysław Homenda. 14th Computer Information Systems and Industrial Management (CISIM), Sep 2015, Warsaw, Poland. Springer, Lecture Notes in Computer Science, LNCS-9339, pp.111-119, 2015, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-24369-6_9〉. 〈hal-01444509〉

Partager

Métriques

Consultations de la notice

38