Decoding phantom limb neuro-mechanical function for a new paradigm of mind-controlled bionic limbs

Massimo Sartori*, Guillaume Durandau, Strahinja Dosen, Dario Farina

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review


    Mind controlled bionic limbs promise to replace mechanical function of lost biological extremities and restore amputees’ motor capacity. State of the art approaches use machine learning for establishing a mapping function between electromyography (EMG) and joint kinematics. However, current approaches require frequent recalibration with lack of robustness, thus providing control paradigms that are sensitive to external conditions. This paper presents an alternative method based on the authors’ recent findings. That is, a biomimetic decoder comprising a computational model that explicitly synthesizes the dynamics of the musculoskeletal system as controlled by EMG-derived neural activation signals.

    Original languageEnglish
    Title of host publicationBiosystems and Biorobotics
    EditorsLorenzo Masia, Silvestro Micera, Metin Akay, Jose L. Pons
    Number of pages4
    ISBN (Electronic)978-3-030-01845-0
    ISBN (Print)978-3-030-01844-3
    Publication statusPublished - 1 Jan 2019
    Event4th International Conference on NeuroRehabilitation, ICNR 2018: Converging Clinical and Engineering Research on Neurorehabilitation III - Pisa, Italy
    Duration: 16 Oct 201820 Oct 2018
    Conference number: 4

    Publication series

    NameBiosystems and Biorobotics
    ISSN (Print)2195-3562
    ISSN (Electronic)2195-3570


    Conference4th International Conference on NeuroRehabilitation, ICNR 2018
    Abbreviated titleICNR
    Internet address


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