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dc.contributor.authorGallagher, William
dc.contributor.authorDing, Ming
dc.contributor.authorUeda, Jun
dc.date.accessioned2015-05-26T18:11:27Z
dc.date.available2015-05-26T18:11:27Z
dc.date.issued2013-06
dc.identifier.citationWilliam Gallagher, Ming Ding, Jun Ueda, “Relaxed Individual Control of Skeletal Muscle Forces via Physical Human-robot Interaction,” Multibody System Dynamics, Vol. 30, Issue 1, pp 77-99, June 2013. DOI: http://dx.doi.org/10.1007/s11044-013-9362-yen_US
dc.identifier.urihttp://hdl.handle.net/1853/53357
dc.descriptionCopyright © Springeren_US
dc.descriptionDOI: http://dx.doi.org/10.1007/s11044-013-9362-y
dc.description.abstractThis study develops a relaxed formulation of a method for controlling individual muscle forces using exoskeleton robots. Past studies have developed a muscle-force control method with very strict limitations on the conditions. These conditions will be removed, and the problem will be reformulated as a constrained optimization of several parameters. The optimization algorithm recognizes when a solution to the muscle control problem cannot be exactly realized, and finds the solution that minimizes the mean errors of the individual muscles between expected and desired muscle activation. This is demonstrated in a computer simulation of human arm dynamics and compared against the prior method to demonstrate its wider applicability. In addition, the control method is extended to resolve issues associated with a nonideal exoskeleton with incomplete torque application to the joints. A quasi-optimized motor-task that minimizes the errors in target muscles and nontarget muscles can be obtained. This paper presents theoretical analysis, simulation, and experimental results on the performance of the relaxed individual muscle control.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectExoskeletonen_US
dc.subjectMuscle isolationen_US
dc.subjectMusculoskeletal modelen_US
dc.titleRelaxed Individual Control of Skeletal Muscle Forces via Physical Human-robot Interactionen_US
dc.typePost-print
dc.contributor.corporatenameGeorgia Institute of Technology. School of Mechanical Engineeringen_US
dc.contributor.corporatenameAdvanced Science Institute, RIKEN. Collaboration Center for Human-Interactive Robot Researchen_US
dc.identifier.doi10.1007/s11044-013-9362-y
dc.embargo.termsnullen_US


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