Literature DB >> 6527290

An analysis of extended physiological proprioception as a prosthesis-control technique.

J A Doubler, D S Childress.   

Abstract

This research was devoted to an investigation of the practicality and potential effectiveness of applying the concept of extended physiological proprioception (EPP) to the control of upper-limb prostheses. The purpose of this study was to verify that EPP control, implemented by coupling prosthesis function to residual shoulder motion in a position-servo relationship, could be effectively applied in multifunctional prostheses for shoulder disarticulation amputees. Although Simpson has shown that the principle works, the authors wanted to quantify its effectiveness and analyze its limitations. Studies were performed analyzing the feasibility of using shoulder elevation-depression and protraction-retraction as prosthesis control inputs. The results of this study showed that a prosthesis mechanism with nonlimiting dynamic response characteristics and shoulder-activated EPP control of wrist rotation and elbow flexion/extension, exhibited functional characteristics comparable to those of the physiological elbow and wrist as defined by tracking capabilities. The results of this investigation also showed that shoulder-effected position control of prosthesis function has considerably more potential for providing effective control than similarly effected velocity control.

Entities:  

Mesh:

Year:  1984        PMID: 6527290

Source DB:  PubMed          Journal:  J Rehabil Res Dev        ISSN: 0748-7711


  12 in total

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Journal:  J Rehabil Res Dev       Date:  2011

3.  Micropower, strain-gauge sampling circuit for prosthetic limb applications.

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Journal:  J Neuroeng Rehabil       Date:  2017-11-06       Impact factor: 4.262

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Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2011-08-30       Impact factor: 3.802

7.  Design and evaluation of a prosthetic shoulder controller.

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Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

Review 8.  The science of neural interface systems.

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Authors:  Chao Mao; Xiaoguang Liu; Yilei Zhang; Guang Lei; Yuelong Yan; Hyemin Lee; Pranavi Koppula; Shiqi Wu; Li Zhuang; Bingliang Fang; Masha V Poyurovsky; Kellen Olszewski; Boyi Gan
Journal:  Nature       Date:  2021-05-12       Impact factor: 49.962

Review 10.  Non-invasive control interfaces for intention detection in active movement-assistive devices.

Authors:  Joan Lobo-Prat; Peter N Kooren; Arno H A Stienen; Just L Herder; Bart F J M Koopman; Peter H Veltink
Journal:  J Neuroeng Rehabil       Date:  2014-12-17       Impact factor: 4.262

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