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: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-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 publicationProceedings of the 4th International Conference on NeuroRehabilitation : ICNR2018
EditorsLorenzo Masia, Silvestro Micera, Metin Akay, José L. Pons
Number of pages4
PublisherSpringer Publishing Company
Publication date1 Jan 2019
ISBN (Print)978-3-030-01844-3
ISBN (Electronic)978-3-030-01845-0
Publication statusPublished - 1 Jan 2019
EventInternational Conference on Neurorehabilitation - Pisa, Italy
Duration: 16 Oct 201820 Oct 2018


ConferenceInternational Conference on Neurorehabilitation
Internet address
SeriesBiosystems and Biorobotics


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