Ghiatt, K., Koh, A. L., Scapucciati, L. ea, & Kinugawa, K. (2024). Gaussianity Evaluation of HD‐sEMG Signals with Aging and Sex During Low and Moderate Isometric Contractions of the Biceps Brachii IRBM, 45, 100851.
References
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2024
MohammadiNasrabadi, A., Moammer, G., Quateen, A., Bhanot, K., & McPhee, J. (2024). Landet: an efficient physics-informed deep learning approach for automatic detection of anatomical landmarks and measurement of spinopelvic alignment Journal of Orthopaedic Surgery and Research, 19. https://doi.org/https://doi.org/10.1186/s13018-024-04654-7
Nasr, A., Bell, S., Whittaker, R. L., Dickerson, C. R., & McPhee, J. (2024). Robust machine learning mapping of sEMG signals to future actuator commands in biomechatronic devices Journal of Bionic Engineering, 21. https://doi.org/https://doi.org/10.1007/s42235-023-00453-8 (Original work published 2024)
Masoudi, R., Taghavipour, A., Azad, N. L., & McPhee, J. (2024). A Robust Model Order Reduction Scheme for Lithium‐Ion Batteries in Control‐ Oriented Vehicle Models Journal of The Electrochemical Society, 171, 053501.
Nasr, A., Bell, S., Whittaker, R. L., & Dickerson, C. R. and. (2024). Robust machine learning mapping of sEMG signals to future actuator commands in biomechatronic devices Journal of Bionic Engineering, 21, 270‐‐287.
2023
MohammadiNasrabadi, A., & McPhee, J. (2023). Preliminary optimization of cup-implant orientation in total-hip arthroplasty using a parametric predictive analysis of lower-limb dynamics influenced by spine stiffness Multibody System Dynamics, 1-26. https://doi.org/https://doi.org/10.1007/s11044-023-09951-3
Krishnan, B., Zanelli, S., Boudaoud, S., Scapucciati, L., McPhee, J., & Jiang, N. (2023). Age-sensitive high density surface electromyogram indices for detecting muscle fatigue using core shape modelling Biomedical Signal Processing and Control, 81. https://doi.org/https://doi.org/10.1016/j.bspc.2022.104446 (Original work published 2023)
Haraguchi, N., Nasr, A., Inkol, K. A., Hase, K., & McPhee, J. (2023). Human and passive lower-limb exoskeleton interaction analysis: Computational study with dynamics simulation using nonlinear model predictive control Presented at the The Society of Instrument and Control Engineers (SICE) Annual Conference conference. Tsu, Japan: IEEE. https://doi.org/https://doi.org/10.23919/SICE59929.2023.10354196 (Original work published 2023)
Nasr, A., Hashemi, A., & McPhee, J. (2023). Scalable musculoskeletal model for dynamic simulations of upper body movement Computer Methods in Biomechanics and Biomedical Engineering, 27. https://doi.org/https://doi.org/10.1080/10255842.2023.2184747 (Original work published 2023)
Laschowski, B., & McPhee, J. (2023). Energy-Efficient Actuator Design Principles for Robotic Leg Prostheses and Exoskeletons: A Review of Series Elasticity and Backdrivability ASME Journal of Computational and Nonlinear Dynamics. https://doi.org/10.1115/1.4056919