title: Intelligent multifunction myoelectric control of hand prostheses.
abstract: Intuitive myoelectric prosthesis control is difficult to achieve due to the absence of proprioceptive feedback, which forces the user to monitor grip pressure by visual information. Existing myoelectric hand prostheses form a single degree of freedom pincer motion that inhibits the stable prehension of a range of objects. Multi-axis hands may address this lack of functionality, but as with multifunction devices in general, serve to increase the cognitive burden on the user. Intelligent hierarchical control of multiple degree-of-freedom hand prostheses has been used to reduce the need for visual feedback by automating the grasping process. This paper presents a hybrid controller that has been developed to enable different prehensile functions to be initiated directly from the user's myoelectric signal. A digital signal processor (DSP) regulates the grip pressure of a new six-degree-of-freedom hand prosthesis thereby ensuring secure prehension without continuous visual feedback.
authors.affiliation: Electronics and Computer Science, University of Southampton, Highfield, Southampton SO17 1BJ, UK.
authors.forename: C M
authors.initials: CM
authors.lastname: Light
authors.forename: P H
authors.initials: PH
authors.lastname: Chappell
authors.forename: B
authors.initials: B
authors.lastname: Hudgins
authors.forename: K
authors.initials: K
authors.lastname: Engelhart
mesh_terms: D000465:Algorithms; D001186:Artificial Limbs; D015374:Biosensing Techniques / Q000295:instrumentation* / Q000379:methods; D004576:Electromyography; D004582:Electronics, Medical / Q000295:instrumentation; D005246:Feedback; D006225:Hand / Q000503:physiopathology*; D018737:Hand Strength; D006801:Humans; D018482:Muscle, Skeletal / Q000503:physiopathology; D016571:Neural Networks, Computer; D011474:Prosthesis Design