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Proprioceptive Sonomyographic Control: A novel method for intuitive and proportional control of multiple degrees-of-freedom for individuals with upper extremity limb loss

Published on Dec 1, 2019in Scientific Reports4.01
· DOI :10.1038/s41598-019-45459-7
Ananya S. Dhawan (GMU: George Mason University), Biswarup Mukherjee3
Estimated H-index: 3
(GMU: George Mason University)
+ 7 AuthorsSiddhartha Sikdar16
Estimated H-index: 16
(GMU: George Mason University)
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Abstract
Technological advances in multi-articulated prosthetic hands have outpaced the development of methods to intuitively control these devices. In fact, prosthetic users often cite "difficulty of use" as a key contributing factor for abandoning their prostheses. To overcome the limitations of the currently pervasive myoelectric control strategies, namely unintuitive proportional control of multiple degrees-of-freedom, we propose a novel approach: proprioceptive sonomyographic control. Unlike myoelectric control strategies which measure electrical activation of muscles and use the extracted signals to determine the velocity of an end-effector; our sonomyography-based strategy measures mechanical muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Therefore, our sonomyography-based control is congruent with a prosthetic user’s innate proprioception of muscle deformation in the residual limb. In this work, we evaluated proprioceptive sonomyographic control with 5 prosthetic users and 5 able-bodied participants in a virtual target achievement and holding task for 5 different hand motions. We observed that with limited training, the performance of prosthetic users was comparable to that of able-bodied participants and thus conclude that proprioceptive sonomyographic control is a robust and intuitive prosthetic control strategy.
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References56
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#1Rayyan Azam Khan (Air University (Islamabad))H-Index: 3
#2Noman Naseer (Air University (Islamabad))H-Index: 12
Last.Muhammad Umer Khan (Air University (Islamabad))H-Index: 2
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#1Linda Resnik (Brown University)H-Index: 23
#2He Huang (UNC: University of North Carolina at Chapel Hill)H-Index: 21
Last.Nancy Wolk (UNC: University of North Carolina at Chapel Hill)H-Index: 1
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#1Yuki Sato (Rits: Ritsumeikan University)H-Index: 1
#2Toshihiro Kawase (TITech: Tokyo Institute of Technology)H-Index: 6
Last.Kenji Kansaku (University of Electro-Communications)H-Index: 20
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#1Amir Khan (GMU: George Mason University)H-Index: 7
#2Ananya S. Dhawan (GMU: George Mason University)
Last.Siddhartha Sikdar (GMU: George Mason University)H-Index: 16
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#1Elizabeth Tarbox (GMU: George Mason University)H-Index: 1
#2Nima Akhlaghi (GMU: George Mason University)H-Index: 3
Last.Siddhartha Sikdar (GMU: George Mason University)H-Index: 16
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Dec 1, 2016 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Ludger van Dijk (UMCG: University Medical Center Groningen)H-Index: 5
Last.Raoul M. BongersH-Index: 18
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#1Nima Akhlaghi (GMU: George Mason University)H-Index: 3
#2Clayton A. Baker (GMU: George Mason University)H-Index: 2
Last.Siddhartha Sikdar (GMU: George Mason University)H-Index: 16
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