Identifying Time-Varying Neuromuscular Response: A Recursive Least-Squares Algorithm with Pseudoinverse

Mario Olivari, Frank M. Nieuwenhuizen, Heinrich Bulthoff, Lorenzo Pollini

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

    2 Citations (Scopus)

    Abstract

    Effectiveness of hap tic guidance systems depends on how humans adapt their neuromuscular response to the force feedback. A quantitative insight into adaptation of neuromuscular response can be obtained by identifying neuromuscular dynamics. Since humans are likely to vary their neuromuscular response during realistic control scenarios, there is a need for methods that can identify time-varying neuromuscular dynamics. In this work an identification method is developed which estimates the impulse response of time-varying neuromuscular system by using a Recursive Least Squares (RLS) method. The proposed method extends the commonly used RLS-based method by employing the pseudo inverse operator instead of the inverse operator. This results in improved robustness to external noise. The method was validated in a human in-The-loop experiment. The neuromuscular estimates given by the proposed method were more accurate than those obtained with the commonly used RLS-based method.

    Original languageEnglish
    Title of host publicationProceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3079-3085
    Number of pages7
    ISBN (Print)9781479986965
    DOIs
    Publication statusPublished - 2016 Jan 12
    EventIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong
    Duration: 2015 Oct 92015 Oct 12

    Other

    OtherIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
    Country/TerritoryHong Kong
    CityKowloon Tong
    Period15/10/915/10/12

    Keywords

    • Haptic AIDS
    • neuromuscular system
    • recursive least squares algorithm
    • timevarying identification

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Networks and Communications
    • Energy Engineering and Power Technology
    • Information Systems and Management
    • Control and Systems Engineering

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