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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)An undercomplete autoencoder to extract muscle synergies for motor intention detection., , , , , , , и . IJCNN, стр. 1-8. IEEE, (2019)Evaluating Efficacy of Continuous Assistance Control During Orientation Tasks with an Active Wrist Exoskeleton., , , , , , и . ICAR, стр. 545-550. IEEE, (2023)A Decision Support System to Provide an Ongoing Prediction of Robot-Assisted Rehabilitation Outcome in Stroke Survivors., , , , , , , и . ICORR, стр. 1-6. IEEE, (2023)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)