Literature DB >> 20593322

Feasibility of controlling prosthetic hand using sonomyography signal in real time: preliminary study.

Jun Shi1, Qian Chang, Yong-Ping Zheng.   

Abstract

The morphological changes of muscle can be accurately detected by sonography, a process we have termed sonomyography (SMG). This article investigates the feasibility of using muscle thickness deformation SMG as a new signal source to control a prosthetic hand in real time. Thickness deformation SMG of the extensor muscle was measured by a block-matching algorithm during wrist extension-flexion; the amplitude of the deformation was used to control the prosthetic hand. We compared various fast-search algorithms to select the best one for real-time prosthetic control. The two-dimensional logarithmic search (TDL) algorithm, with and without streaming single-instruction multiple-data extensions, showed excellent execution efficiency, with an overall mean correlation coefficient of about 0.99, a mean standard root-mean-square error <0.75, and a mean relative root-mean-square error <8.0% referenced to the cross-correlation algorithm baseline. The mean frame rates were greater than the ultrasound sampling rate (12 Hz), indicating that TDL could be implemented in real-time control. These results demonstrate that only one muscle position is needed to control a prosthetic hand, allowing for proprioception of muscle tension, and that the SMG provides good control of the prosthetic hand, allowing it to proportionally open and close with a fast-search algorithm.

Mesh:

Year:  2010        PMID: 20593322     DOI: 10.1682/jrrd.2009.03.0031

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


  8 in total

1.  First Demonstration of Functional Task Performance Using a Sonomyographic Prosthesis: A Case Study.

Authors:  Susannah M Engdahl; Samuel A Acuña; Erica L King; Ahmed Bashatah; Siddhartha Sikdar
Journal:  Front Bioeng Biotechnol       Date:  2022-05-04

Review 2.  A review of non-invasive techniques to detect and predict localised muscle fatigue.

Authors:  Mohamed R Al-Mulla; Francisco Sepulveda; Martin Colley
Journal:  Sensors (Basel)       Date:  2011-03-24       Impact factor: 3.576

Review 3.  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

4.  Electromyography and sonomyography analysis of the tibialis anterior: a cross sectional study.

Authors:  Antonio I Cuesta-Vargas; Maria Ruiz-Muñoz
Journal:  J Foot Ankle Res       Date:  2014-02-08       Impact factor: 2.303

5.  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

6.  Localization accuracy of multiple magnets in a myokinetic control interface.

Authors:  Marta Gherardini; Francesco Clemente; Stefano Milici; Christian Cipriani
Journal:  Sci Rep       Date:  2021-03-01       Impact factor: 4.996

7.  Evaluating Electromyography and Sonomyography Sensor Fusion to Estimate Lower-Limb Kinematics Using Gaussian Process Regression.

Authors:  Kaitlin G Rabe; Nicholas P Fey
Journal:  Front Robot AI       Date:  2022-03-21

Review 8.  Mechanomyogram for muscle function assessment: a review.

Authors:  Md Anamul Islam; Kenneth Sundaraj; R Badlishah Ahmad; Nizam Uddin Ahamed
Journal:  PLoS One       Date:  2013-03-11       Impact factor: 3.240

  8 in total

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