Febrer-Nafría, M., Nasr, A., Ezati, M., Brown, P., Font-Llagunes, J. M., & McPhee, J. (2022). Predictive multibody dynamic simulation of human neuromusculoskeletal systems: a review Multibody System Dynamics. https://doi.org/https://doi.org/10.1007/s11044-022-09852-x (Original work published 2022)
References
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2022
McPhee, J. (2022). A review of dynamic models and measurements in golf Sports Engineering, 25, 1-19. https://doi.org/https://doi.org/10.1007/s12283-022-00387-0 (Original work published 2022)
Laschowski, B., McNally, W., Wong, A., & McPhee, J. (2022). Environment Classification for Robotic Leg Prostheses and Exoskeletons using Deep Convolutional Neural Networks Frontiers in Neurorobotics, 15. https://doi.org/10.3389/fnbot.2021.730965 (Original work published 2022)
Nasr, A., Ferguson, S., & McPhee, J. (2022). Model-based design and optimization of passive shoulder exoskeletons J. Comput. Nonlinear Dynam., 17. https://doi.org/10.1115/1.4053405 (Original work published 2022)
2021
Nasr, A., Inkol, K. A., Bell, S., & McPhee, J. (2021). InverseMuscleNET: alternative machine learning solution to static optimization and inverse muscle modeling Frontiers in Computational Neuroscience, 15, 759489.
Nasr, A., Inkol, K. A., Bell, S., & McPhee, J. (2021). InverseMuscleNET: Alternative machine learning solution to static optimization and inverse muscle modeling Frontiers in Computational Neuroscience. https://doi.org/10.3389/fncom.2021.759489 (Original work published 2021)
Zhao, J., Li, X., Shum, C., & McPhee, J. (2021). A review of physics‐based and data‐driven models for real‐time control of polymer electrolyte membrane fuel cells Energy and AI, 6, 100114.
Masoudi, R., & McPhee, J. (2021). Application of Karhunen‐‐Lo\ eve decomposition and piecewise linearization to a physics‐based battery model Electrochimica Acta, 365, 137093.
Zhao, J., Li, X., Shum, C., & McPhee, J. (2021). A review of physics‐based and data‐driven models for real‐time control of polymer electrolyte membrane fuel cells Energy and AI, 6, 100114.
Nasr, A., Bell, S., He, J., Whittaker, R. L., Jiang, N., Dickerson, C. R., & McPhee, J. (2021). MuscleNET: Mapping electromyography to kinematic and dynamic biomechanical variables by machine learning Journal of Neural Engineering. https://doi.org/10.1088/1741-2552/ac1adc (Original work published 2021)