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[DOI: 10.1109/BioRob60516.2024.10719875]. Integrate this neural information into real-time musculoskeletal modeling using our CEINMS-RT framework [DOI: 10.36227/techrxiv.173397962.28177284/v1]. Enable
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forefront of neuromechanics and assistive robotics. Our work bridges neuroscience, biomechanics, and robotics to develop real-time models of joint biomechanics and adaptive control strategies for wearable
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, analysis, and model choice while retaining strong error guarantees. This means that researchers can adapt their research questions and sampling plans to the data as they come in and in a way that is as model
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