Segmentation of human body movement using inertial measurement unit

Takashi Aoki, Gentiane Venture, Dana Kulić

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

10 Citations (Scopus)

Abstract

This paper proposes an approach for the temporal segmentation of human body movements using IMU (Inertial Measurement Unit). The approach is based on online HMM-based segmentation of continuous time series data. In previous studies, the real-time segmentation of human body movement using joint angles acquired by optical motion capture has been realized, using stochastic motion modeling. The approach is now adapted for angular velocity data. The segmented motions are recognized via HMM models. The segmentation and recognition results of the proposed algorithm are demonstrated with experiments. Auto segmentation of each motion and recognition of motion patterns are verified using angular velocity data obtained by IMU sensors and the Wii remote. The success rate of auto segmentation using the data obtained by Wii remote was more than 80% on average.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1181-1186
Number of pages6
ISBN (Print)9780769551548
DOIs
Publication statusPublished - 1 Dec 2013
Externally publishedYes
EventIEEE International Conference on Systems, Man and Cybernetics 2013 - Manchester, United Kingdom
Duration: 13 Oct 201316 Oct 2013
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6689802 (IEEE Conference Proceedings)

Publication series

NameProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013

Conference

ConferenceIEEE International Conference on Systems, Man and Cybernetics 2013
Abbreviated titleSMC 2013
Country/TerritoryUnited Kingdom
CityManchester
Period13/10/1316/10/13
Internet address

Keywords

  • Arm motion
  • HMM
  • Inertial measurement unit
  • Recognition
  • Segmentation
  • Wii remote

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