Control Applications for Biomedical Engineering Systems

Control Applications for Biomedical Engineering Systems presents different control engineering and modeling applications in the biomedical field. It is intended for senior undergraduate or graduate students in both control engineering and biomedical engineering programs. For control engineering students, it presents the application of various techniques already learned in theoretical lectures in the biomedical arena. For biomedical engineering students, it presents solutions to various problems in the field using methods commonly used by control engineers.

Points out theoretical and practical issues to biomedical control systemsBrings together solutions developed under different settings with specific attention to the validation of these tools in biomedical settings using real-life datasets and experimentsPresents significant case studies on devices and applications

1. Neuro-fuzzy inverse optimal control incorporating a multistep predictor as applied to T1DM patients 2. Blood glucose regulation in patients with type 1 diabetes by means of output-feedback sliding mode control 3. Impulsive MPC schemes for biomedical processes: Application to type 1 diabetes 4. Robust control applications in biomedical engineering: Control of depth of hypnosis 5. Robust control strategy for HBV treatment: Considering parametric and nonparametric uncertainties 6. A closed loop robust control system for electrosurgical generators 7. Application of a T-S unknown input observer for studying sitting control for people living with spinal cord injury 8. Epidemic modeling and control of HIV/AIDS dynamics in populations under external interactions: A worldwide challenge 9. Reinforcement learning-based control of drug dosing with applications to anesthesia and cancer therapy 10. Control strategies in general anesthesia administration 11. Computational modeling of the control mechanisms involved in the respiratory system 12. Intelligent decision support for lung ventilation 13. Customized modeling and optimal control of superovulation stage in in vitro fertilization (IVF) treatment 14. Models based on cellular automata for the analysis of biomedical systems