Intelligent multifunction myoelectric control of hand prostheses

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...

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Published in:Journal of medical engineering & technology 2002-07, Vol.26 (4), p.139-146
Main Authors: Light, C. M., Chappell, P. H., Hudgins, B., Engelhart, K.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Limbs
Biological and medical sciences
Biosensing Techniques - instrumentation
Biosensing Techniques - methods
Electromyography
Electronics, Medical - instrumentation
Feedback
Hand - physiopathology
Hand Strength
Humans
Medical sciences
Muscle, Skeletal - physiopathology
Neural Networks (Computer)
Prosthesis Design
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container_end_page 146
container_issue 4
container_start_page 139
container_title Journal of medical engineering & technology
container_volume 26
creator Light, C. M.
Chappell, P. H.
Hudgins, B.
Engelhart, K.
description 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.
doi_str_mv 10.1080/03091900210142459
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source Taylor and Francis:Jisc Collections:Taylor and Francis Read and Publish Agreement 2024-2025:Medical Collection (Reading list)
subjects Algorithms
Artificial Limbs
Biological and medical sciences
Biosensing Techniques - instrumentation
Biosensing Techniques - methods
Electromyography
Electronics, Medical - instrumentation
Feedback
Hand - physiopathology
Hand Strength
Humans
Medical sciences
Muscle, Skeletal - physiopathology
Neural Networks (Computer)
Prosthesis Design
title Intelligent multifunction myoelectric control of hand prostheses
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