title: An optimized proportional-derivative controller for the human upper extremity with gravity.
abstract: When Functional Electrical Stimulation (FES) is used to restore movement in subjects with spinal cord injury (SCI), muscle stimulation patterns should be selected to generate accurate and efficient movements. Ideally, the controller for such a neuroprosthesis will have the simplest architecture possible, to facilitate translation into a clinical setting. In this study, we used the simulated annealing algorithm to optimize two proportional-derivative (PD) feedback controller gain sets for a 3-dimensional arm model that includes musculoskeletal dynamics and has 5 degrees of freedom and 22 muscles, performing goal-oriented reaching movements. Controller gains were optimized by minimizing a weighted sum of position errors, orientation errors, and muscle activations. After optimization, gain performance was evaluated on the basis of accuracy and efficiency of reaching movements, along with three other benchmark gain sets not optimized for our system, on a large set of dynamic reaching movements for which the controllers had not been optimized, to test ability to generalize. Robustness in the presence of weakened muscles was also tested. The two optimized gain sets were found to have very similar performance to each other on all metrics, and to exhibit significantly better accuracy, compared with the three standard gain sets. All gain sets investigated used physiologically acceptable amounts of muscular activation. It was concluded that optimization can yield significant improvements in controller performance while still maintaining muscular efficiency, and that optimization should be considered as a strategy for future neuroprosthesis controller design.
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; Fluid Physics and Transport Processes Branch, NASA Glenn Research Center, Cleveland, OH, United States; Center for Space Medicine, Baylor College of Medicine, Houston, TX, United States. Electronic address: kathleen.jagodnik@nasa.gov.
authors.forename: Kathleen M
authors.initials: KM
authors.lastname: Jagodnik
authors.affiliation: Institute for Science and Technology in Medicine, Keele University, UK.
authors.forename: Dimitra
authors.initials: D
authors.lastname: Blana
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; Department of Mechanical Engineering, Fenn College of Engineering, Cleveland State University, Cleveland, OH, United States; Orchard Kinetics, LLC, Cleveland, OH, United States.
authors.forename: Antonie J
authors.initials: AJ
authors.lastname: van den Bogert
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; Cleveland Functional Electrical Stimulation (FES) Center, Cleveland, OH, United States; Louis Stokes Cleveland Veterans Administration Medical Center, Cleveland, OH, United States; MetroHealth Medical Center, Cleveland, OH, United States.
authors.forename: Robert F
authors.initials: RF
authors.lastname: Kirsch
mesh_terms: D000465:Algorithms; D001132:Arm / Q000502:physiology; D004558:Electric Stimulation; D004599:Electric Stimulation Therapy; D005246:Feedback; D006112:Gravitation; D006801:Humans; D008297:Male; D008954:Models, Biological; D009068:Movement / Q000502:physiology; D018763:Muscle Fatigue; D018482:Muscle, Skeletal / Q000502:physiology*; D009132:Muscles; D013119:Spinal Cord Injuries / Q000628:therapy*; D034941:Upper Extremity / Q000502:physiology*
keywords: Feedback control; Functional electrical stimulation; Human; Musculoskeletal modeling and simulation; Optimization; Proportional-derivative; Upper extremity