Methodology for automatic movement cycle extraction using Switching Linear Dynamic System

Roberto De Souza Baptista, Antônio Padilha Lanari Bó, Mitsuhiro Hayashibe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Human motion assessment is key for motor-control rehabilitation. Using standardized definitions and spatiotemporal features - usually presented as a movement cycle diagram- specialists can associate kinematic measures to progress in rehabilitation therapy or motor impairment due to trauma or disease. Although devices for capturing human motion today are cheap and widespread, the automatic interpretation of kinematic data for rehabilitation is still poor in terms of quantitative performance evaluation. In this paper we present an automatic approach to extract spatiotemporal features from kinematic data and present it as a cycle diagram. This is done by translating standard definitions from human movement analysis into mathematical elements of a Switching Linear Dynamic System model. The result is a straight-forward procedure to learn a tracking model from a sample execution. This model is robust when used to automatically extract the movement cycle diagram of the same motion (the Sit-Stand-Sit, as an example) executed in different subject-specific manner such as his own motion speed.

Original languageEnglish
Title of host publication2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PublisherIEEE Computer Society
Pages743-746
Number of pages4
ISBN (Electronic)9781467363891
DOIs
Publication statusPublished - 2015 Jul 1
Event7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France
Duration: 2015 Apr 222015 Apr 24

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2015-July
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
CountryFrance
CityMontpellier
Period15/4/2215/4/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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  • Cite this

    De Souza Baptista, R., Padilha Lanari Bó, A., & Hayashibe, M. (2015). Methodology for automatic movement cycle extraction using Switching Linear Dynamic System. In 2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 (pp. 743-746). [7146730] (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2015-July). IEEE Computer Society. https://doi.org/10.1109/NER.2015.7146730