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Towards online myoelectric control based on muscle synergies-to-force mapping for robotic applications.

, , , , и . Neurocomputing, (2021)

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Cristian Sommariva

Cristian Chitu

Cristian Picioreanu

Cristian Weiss

Cristian Pellizzer

 

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Gait Phases Blended Control for Enhancing Transparency on Lower-Limb Exoskeletons., , , , , и . IEEE Robotics Autom. Lett., 6 (3): 5453-5460 (2021)A Random Tree Forest decision support system to personalize upper extremity robot-assisted rehabilitation in stroke: a pilot study., , , , , , , и . ICORR, стр. 1-6. IEEE, (2022)Identification of Gait Phases with Neural Networks for Smooth Transparent Control of a Lower Limb Exoskeleton., , , и . ICINCO, стр. 171-178. SCITEPRESS, (2021)Investigating muscle synergies changes after rehabilitation robotics training on stroke survivors: a pilot study*., , , и . EMBC, стр. 3731-3734. IEEE, (2020)Task-Oriented Muscle Synergy Extraction Using An Autoencoder-Based Neural Model., , , , , и . Information, 11 (4): 219 (2020)How Many Muscles? Optimal Muscles Set Search for Optimizing Myocontrol Performance., , , , и . Frontiers Comput. Neurosci., (2021)Wearable Haptics in a Modern VR Rehabilitation System: Design Comparison for Usability and Engagement., , , и . EuroHaptics, том 13235 из Lecture Notes in Computer Science, стр. 274-282. Springer, (2022)Evaluating Generalization Capability of Bio-inspired Models for a Myoelectric Control: A Pilot Study., , , , , и . ICIC (3), том 11645 из Lecture Notes in Computer Science, стр. 739-750. Springer, (2019)Towards online myoelectric control based on muscle synergies-to-force mapping for robotic applications., , , , и . Neurocomputing, (2021)EXOSMOOTH: Test of Innovative EXOskeleton Control for SMOOTH Assistance, With and Without Ankle Actuation., , , , , и . HRI, стр. 890-894. IEEE / ACM, (2022)