@article {999,
	title = {Robust machine learning mapping of sEMG signals to future actuator commands in biomechatronic devices},
	journal = {Journal of Bionic Engineering},
	volume = {21},
	year = {2024},
	month = {01/2024},
	chapter = {270-287},
	keywords = {Bionic, Exoskeleton, Machine Learning, Multibody System Dynamics, Myoelectric-based control, Surface electromyography},
	doi = {https://doi.org/10.1007/s42235-023-00453-8},
	author = {Ali Nasr and Sydney Bell and Rachel L. Whittaker and Clark R. Dickerson and John McPhee}
}
@inproceedings {921,
	title = {Model-based design and optimization of passive shoulder exoskeletons},
	booktitle = {ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference},
	year = {2021},
	publisher = {ASME},
	organization = {ASME},
	abstract = {<p>To physically assist workers in reducing musculoskeletal strain or to develop motor skills for patients with neuromuscular disabilities, recent research has focused on Exoskeletons (Exos). Designing active Exos is challenging due to the complex human geometric structure, the human-Exoskeleton wrench interaction, the kinematic constraints, and the selection of power source characteristics. Because of the portable advantages of passive Exos, designing a passive shoulder mechanism has been studied here. The study concentrates on modeling a 3D multibody upper-limb human-Exoskeleton, developing a procedure of analyzing optimal assistive torque profiles, and optimizing the passive mechanism features for desired tasks. The optimization objective is minimizing the human joint torques. For simulating the complex closed-loop multibody dynamics, differential-algebraic equations (DAE)s of motion have been generated and solved. Three different tasks have been considered, which are common in industrial environments: object manipulation, over-head work, and static pointing. The resulting assistive Exoskeleton\&rsquo;s elevation joint torque profile could decrease the specific task\&rsquo;s human shoulder torque. Since the passive mechanism produces a specific torque for a given elevation angle, the Exoskeleton is not versatile or optimal for different dynamic tasks. We concluded that designing a passive Exoskeleton for a wide range of dynamic applications is impossible. We hypothesize that augmenting an actuator to the mechanism can provide the necessary adjustment torque and versatility for multiple tasks.</p>
},
	keywords = {Exoskeletons, Multibody System Dynamics, Optimization, Wearable Robotics},
	author = {Ali Nasr and Spencer Ferguson and John McPhee}
}
@article {843,
	title = {Symbolic Integration of Multibody System Dynamics with the Finite Element Method},
	journal = {Multibody System Dynamics},
	volume = {43},
	year = {2018},
	month = {08/2018},
	abstract = {<p>With the widespread use of computer-aided engineering (CAE) to solve computational mechanics problems, engineering design has become more accurate and efficient. The integration of the finite element method (FEM) and flexible multibody dynamics (FMD) is a typical application of computational mechanics. It constitutes an important contribution to engineering development, but its potential is restrained by numerical computation. Computational time is a critical factor that influences the efficiency and cost of design and analysis. The advent of symbolic computation enables faster simulation code, but the symbolic integration of FEM and FMD is at the initial stages. A general symbolic integration procedure is presented in this paper. The performance of the symbolic model is compared with models from the literature and numerically-based commercial software.</p>
},
	keywords = {Computer-Aided Engineering, Engineering Design, Finite Element Method, Multibody System Dynamics, Symbolic Integration},
	issn = {1573-272X},
	doi = {10.1007/s11044-018-9627-6},
	url = {https://link.springer.com/article/10.1007/s11044-018-9627-6},
	author = {Yiteng Liang and John McPhee}
}
