Improved estimation of starting times of human activities using Hidden Markov modeling based activity classification?

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    Abstract

    Automated classification of human activities should help the researcher, or the physician, with the interpretation of data. In a previous study a novel activity classifier based on Hidden Markov Models was successfully implemented and tested on ambulatory obtained of human activities. The estimated starting times were not accurate. Here the addition of timing information to perform isolated activity training as initialization of the HMM's is proposed to more accurately estimate the starting times of activities.
    Original languageUndefined
    Title of host publicationInternational conference on ambulatory monitoring of physical activity and movement, conference book
    EditorsJ.B.J Bussmann, H.L.D. Horemans, H.L.P. Hurkmans
    Place of PublicationRotterdam
    PublisherErasmus MC
    Pages90
    Number of pages1
    ISBN (Print)978-90-813154-1-8
    Publication statusPublished - 24 May 2008
    Event1st International Conference on Ambulatory Monitoring of Physical Activity and Movement, ICAMPAM 2008 - Rotterdam, Netherlands
    Duration: 21 May 200824 May 2008
    Conference number: 1
    https://ismpb.org/2008-rotterdam/

    Publication series

    Name
    PublisherDept. of Rehabilitation Medicine Erasmus MC
    NumberDTR08-9

    Conference

    Conference1st International Conference on Ambulatory Monitoring of Physical Activity and Movement, ICAMPAM 2008
    Abbreviated titleICAMPAM
    Country/TerritoryNetherlands
    CityRotterdam
    Period21/05/0824/05/08
    Internet address

    Keywords

    • EWI-13250
    • IR-62427
    • METIS-251139
    • BSS-Biomechatronics and rehabilitation technology

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