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MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand., , , , , , , , , и 19 other автор(ы). NeurIPS (Competition and Demos), том 220 из Proceedings of Machine Learning Research, стр. 233-250. PMLR, (2021)Estimation of Time-Varying Ankle Joint Stiffness Under Dynamic Conditions via System Identification Techniques., , , , , и . EMBC, стр. 2119-2122. IEEE, (2019)Myoelectric model-based control of a bi-lateral robotic ankle exoskeleton during even ground locomotion *., , , и . BioRob, стр. 822-826. IEEE, (2020)Model-Based Estimation of Ankle Joint Stiffness During Dynamic Tasks: a Validation-Based Approach., , , , , и . EMBC, стр. 4104-4107. IEEE, (2019)Toward Muscle-Driven Control of Wearable Robots: A Real-Time Framework for the Estimation of Neuromuscular States During Human-Exoskeleton Locomotion Tasks., , , и . BioRob, стр. 683-688. IEEE, (2018)MyoSim: Fast and physiologically realistic MuJoCo models for musculoskeletal and exoskeletal studies., , , , и . ICRA, стр. 8104-8111. IEEE, (2022)Synergy-Driven Musculoskeletal Modeling to Estimate Muscle Excitations and Joint Moments at Different Walking Speeds in Individuals with Transtibial Amputation., , , , и . ICORR, стр. 1-6. IEEE, (2023)MyoSuite: A Contact-rich Simulation Suite for Musculoskeletal Motor Control., , , , и . L4DC, том 168 из Proceedings of Machine Learning Research, стр. 492-507. PMLR, (2022)Toward a Unified Framework for EMG Signals Processing and Controlling an Exoskeleton., и . CRV, стр. 291-298. IEEE Computer Society, (2014)