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)
References
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2022
Lin, Y., McPhee, J., & Azad, N. L. (2022). Co‐optimization of on‐ramp merging and plug‐in hybrid electric vehicle power split using deep reinforcement learning IEEE Transactions on Vehicular Technology, 71, 6958‐‐6968.
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)
Nasr, A., Hashemi, A., & McPhee, J. (2022). Model-based mid-level regulation for assist-as-needed hierarchical control of wearable robots: A computational study of human-robot adaptation Robotics, 11. https://doi.org/10.3390/robotics11010020 (Original work published 2022)
2021
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)
McNally, W., Vats, K., Wong, A., & McPhee, J. (2021). EvoPose2D: Pushing the boundaries of 2d human pose estimation using accelerated neuroevolution with weight transfer IEEE Access, 9, 139403‐‐139414.
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.
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.