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    Sit-to-stand intention recognition

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    Authors
    Wang, Zuobin
    Li, Dayou
    Lu, Hang
    Qiu, Renxi
    Maple, Carsten
    Affiliation
    University of Bedfordshire
    Changchun University of Science and Technology
    Warwick University
    Issue Date
    2021-01-23
    Subjects
    robot
    neural networks
    intention recognition
    prediction
    uncertainty handling
    STS
    sit-to-stand
    
    Metadata
    Show full item record
    Other Titles
    Advanced Manufacturing and Automation X. IWAMA 2020.
    Abstract
    Sit-to-stand (STS) difficulties are common among elderly because of the decline of their cognitive capabilities and motor functions. The way to help is to encourage them to practice their own functions and to assist only at the point where they need during STS processes. The provision of such support requires the elderly’s intention of standing up to be recognised and the amount of support as well as the moment when the support would be needed to be predicted. The research presented in this paper focuses on intention recognition as it is difficult due to uncertainties existing in STS processes and differences in individual’s biomechanical features. This paper presents fuzzy logic based self-adaptive approach to the recognition of standing up intention from sensor signals that contain the uncertainties.
    Citation
    Li D, Lu H, Qiu R, Maple C, Wang Z (2021) 'Sit-to-stand intention recognition', in Wang Y, Martinsen K, Yu T, Wang K (ed(s).). Advanced Manufacturing and Automation X. IWAMA 2020., edn, : Springer Science and Business Media Deutschland GmbH pp.65-72.
    Publisher
    Springer Science and Business Media Deutschland GmbH
    URI
    http://hdl.handle.net/10547/624890
    DOI
    10.1007/978-981-33-6318-2_8
    Additional Links
    https://link.springer.com/chapter/10.1007%2F978-981-33-6318-2_8
    Type
    Book chapter
    Language
    en
    ISBN
    9789813363175
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-981-33-6318-2_8
    Scopus Count
    Collections
    Computing

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