Literature DB >> 25570045

Extending mode switching to multiple degrees of freedom in hand prosthesis control is not efficient.

Sebastian Amsuess, Peter Goebel, Bernhard Graimann, Dario Farina.   

Abstract

In recent years, many sophisticated control strategies for multifunctional dexterous hand prostheses have been developed. It was indeed assumed that control mechanisms based on switching between degrees of freedom, which are in use since the 1960's, could not be extended to efficient control of more than two degrees of freedom. However, quantitative proof for this assumption has not been shown. In this study, we adopted the mode switching paradigm available in commercial prostheses for two degree of freedom control and we extended it for the control of seven functions (3.5 degrees of freedom) in a modern robotic hand. We compared the controllability of this scaled version of the standard method to a state of the art pattern recognition based control in an applied online study. The aim was to quantify whether multi-functional prosthetic control with mode switching outperformed pattern recognition in the control of a real prosthetic hand for daily life activities online. Although in simple grasp-release tasks the conventional method performed best, tasks requiring more complex control of multiple degrees of freedom required a more intuitive control method, such as pattern recognition, for achieving high performance.

Mesh:

Year:  2014        PMID: 25570045     DOI: 10.1109/EMBC.2014.6943677

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  7 in total

1.  Preliminary Evaluation of the Effect of Mechanotactile Feedback Location on Myoelectric Prosthesis Performance Using a Sensorized Prosthetic Hand.

Authors:  Eric D Wells; Ahmed W Shehata; Michael R Dawson; Jason P Carey; Jacqueline S Hebert
Journal:  Sensors (Basel)       Date:  2022-05-21       Impact factor: 3.847

2.  A comparative analysis of three non-invasive human-machine interfaces for the disabled.

Authors:  Vikram Ravindra; Claudio Castellini
Journal:  Front Neurorobot       Date:  2014-10-27       Impact factor: 2.650

3.  Development of a Parent Wireless Assistive Interface for Myoelectric Prosthetic Hands for Children.

Authors:  Yutaro Hiyoshi; Yuta Murai; Yoshiko Yabuki; Kenichi Takahana; Soichiro Morishita; Yinlai Jiang; Shunta Togo; Shinichiro Takayama; Hiroshi Yokoi
Journal:  Front Neurorobot       Date:  2018-08-02       Impact factor: 2.650

4.  Development of an Embedded Myokinetic Prosthetic Hand Controller.

Authors:  Francesco Clemente; Valerio Ianniciello; Marta Gherardini; Christian Cipriani
Journal:  Sensors (Basel)       Date:  2019-07-17       Impact factor: 3.847

5.  A Multi-DoF Prosthetic Hand Finger Joint Controller for Wearable sEMG Sensors by Nonlinear Autoregressive Exogenous Model.

Authors:  Zhaolong Gao; Rongyu Tang; Qiang Huang; Jiping He
Journal:  Sensors (Basel)       Date:  2021-04-07       Impact factor: 3.576

6.  Myoelectric prosthesis users and non-disabled individuals wearing a simulated prosthesis exhibit similar compensatory movement strategies.

Authors:  Heather E Williams; Craig S Chapman; Patrick M Pilarski; Albert H Vette; Jacqueline S Hebert
Journal:  J Neuroeng Rehabil       Date:  2021-05-01       Impact factor: 4.262

7.  The myokinetic control interface: tracking implanted magnets as a means for prosthetic control.

Authors:  S Tarantino; F Clemente; D Barone; M Controzzi; C Cipriani
Journal:  Sci Rep       Date:  2017-12-07       Impact factor: 4.379

  7 in total

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