Intensity analysis of surface myoelectric signals from lower limbs during key gait phases by wavelets in time-frequency

Jiangang Yang, Xuan Gao, Baikun Wan, Dong Ming, Xiaoman Cheng, Hongzhi Qi, Xingwei An, Long Chen, Shuang Qiu, Weijie Wang

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

    Abstract

    This paper presented a time-frequency intensity analysis feature extraction approach of lower limb sEMG (Surface Electromyogram) to identify the key gait phases during walking. The proposed feature extraction method used a filter bank of non-linearly scaled wavelets with specified time-resolution to extract time-frequency aspects of the signal.The intensity analysis algorithm was tested on sEMG data collected from ten healthy young volunteers during 30 walking circles for each. Each walking cycle was made up of four key gait phases:L-DS(Left Double Stance), L-SS(Left Single Stance),R-DS(Right Double Stance),R-SS(Right Single Stance).The identification accuracy of 7 subjects using intensity analysis reached 97%, even up to 99.42%.The others were about 95%. The algorithm obviously achieved a higher accuracy of sEMG recognition than the other algorithms such as root mean square and AR Coefficient. In the future, the feature of sEMG signal under different key gait phases may be used in the control of Functional Electrical Stimulation (FES) and other intelligent artificial limbs.
    Original languageEnglish
    Title of host publicationUniversal Access in Human-Computer Interaction
    Subtitle of host publicationApplications and Services 6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings
    EditorsConstantine Stephanidis
    Place of PublicationBerlin
    PublisherSpringer
    Pages479-488
    Number of pages10
    VolumePart 4
    ISBN (Electronic)9783642216572
    ISBN (Print)9783642216565
    DOIs
    Publication statusPublished - 2011
    Event6th International Conference on Universal Access in Human-Computer Interaction - Orlando, United States
    Duration: 9 Jul 201114 Jul 2011
    http://www.hcii2011.org/

    Publication series

    NameLecture notes in computer science
    PublisherSpringer
    Volume6768
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference6th International Conference on Universal Access in Human-Computer Interaction
    Abbreviated titleUAHCI 2011
    CountryUnited States
    CityOrlando
    Period9/07/1114/07/11
    OtherHeld as Part of HCI International 2011
    Internet address

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    Keywords

    • Feature extraction methods
    • Functional electrical stimulation
    • Gait phasis
    • Identification accuracy
    • Intensity analysis
    • Lower limb
    • Myoelectric signals
    • Other algorithms
    • Root Mean Square
    • Surface electromyogram
    • Time frequency
    • Time-resolution

    Cite this

    Yang, J., Gao, X., Wan, B., Ming, D., Cheng, X., Qi, H., An, X., Chen, L., Qiu, S., & Wang, W. (2011). Intensity analysis of surface myoelectric signals from lower limbs during key gait phases by wavelets in time-frequency. In C. Stephanidis (Ed.), Universal Access in Human-Computer Interaction: Applications and Services 6th International Conference, UAHCI 2011, Held as Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings (Vol. Part 4, pp. 479-488). (Lecture notes in computer science; Vol. 6768). Springer . https://doi.org/10.1007/978-3-642-21657-2_52