title: A control system for a powered prosthesis using positional and myoelectric inputs from the shoulder complex.
abstract: The integration of multiple input sources within a control strategy for powered upper limb prostheses could provide smoother, more intuitive multi-joint reaching movements based on the user's intended motion. The work presented in this paper presents the results of using myoelectric signals (MES) of the shoulder area in combination with the position of the shoulder as input sources to multiple linear discriminant analysis classifiers. Such an approach may provide users with control signals capable of controlling three degrees of freedom (DOF). This work is another important step in the development of hybrid systems that will enable simultaneous control of multiple degrees of freedom used for reaching tasks in a prosthetic limb.
authors.affiliation: Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB Canada. yves.losier@unb.ca
authors.forename: Y
authors.initials: Y
authors.lastname: Losier
authors.forename: K
authors.initials: K
authors.lastname: Englehart
authors.forename: B
authors.initials: B
authors.lastname: Hudgins
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000674:Amputees / Q000534:rehabilitation; D001185:Artificial Intelligence; D011211:Electric Power Supplies; D004576:Electromyography / Q000295:instrumentation / Q000379:methods*; D019544:Equipment Failure Analysis; D005246:Feedback; D006801:Humans; D007595:Joint Prosthesis; D009068:Movement / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011474:Prosthesis Design; D012782:Shoulder / Q000502:physiology*; D013647:Task Performance and Analysis; D013813:Therapy, Computer-Assisted / Q000379:methods