Literature DB >> 25102286

First-in-man demonstration of a fully implanted myoelectric sensors system to control an advanced electromechanical prosthetic hand.

Paul F Pasquina1, Melissa Evangelista2, A J Carvalho3, Joseph Lockhart2, Sarah Griffin3, George Nanos4, Patricia McKay5, Morten Hansen2, Derek Ipsen4, James Vandersea6, Josef Butkus4, Matthew Miller4, Ian Murphy3, David Hankin2.   

Abstract

BACKGROUND: Advanced motorized prosthetic devices are currently controlled by EMG signals generated by residual muscles and recorded by surface electrodes on the skin. These surface recordings are often inconsistent and unreliable, leading to high prosthetic abandonment rates for individuals with upper limb amputation. Surface electrodes are limited because of poor skin contact, socket rotation, residual limb sweating, and their ability to only record signals from superficial muscles, whose function frequently does not relate to the intended prosthetic function. More sophisticated prosthetic devices require a stable and reliable interface between the user and robotic hand to improve upper limb prosthetic function. NEW
METHOD: Implantable Myoelectric Sensors (IMES(®)) are small electrodes intended to detect and wirelessly transmit EMG signals to an electromechanical prosthetic hand via an electro-magnetic coil built into the prosthetic socket. This system is designed to simultaneously capture EMG signals from multiple residual limb muscles, allowing the natural control of multiple degrees of freedom simultaneously.
RESULTS: We report the status of the first FDA-approved clinical trial of the IMES(®) System. This study is currently in progress, limiting reporting to only preliminary results. COMPARISON WITH EXISTING
METHODS: Our first subject has reported the ability to accomplish a greater variety and complexity of tasks in his everyday life compared to what could be achieved with his previous myoelectric prosthesis.
CONCLUSION: The interim results of this study indicate the feasibility of utilizing IMES(®) technology to reliably sense and wirelessly transmit EMG signals from residual muscles to intuitively control a three degree-of-freedom prosthetic arm.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  IMES(®); Implantable devices; Implantable electrodes; Myoelectric; Prosthesis

Mesh:

Year:  2014        PMID: 25102286      PMCID: PMC4317373          DOI: 10.1016/j.jneumeth.2014.07.016

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  14 in total

1.  Establishing a standardized clinical assessment tool of pathologic and prosthetic hand function: normative data, reliability, and validity.

Authors:  Colin M Light; Paul H Chappell; Peter J Kyberd
Journal:  Arch Phys Med Rehabil       Date:  2002-06       Impact factor: 3.966

2.  Save that arm: a study of problems in the remaining arm of unilateral upper limb amputees.

Authors:  L E Jones; J H Davidson
Journal:  Prosthet Orthot Int       Date:  1999-04       Impact factor: 1.895

3.  The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee.

Authors:  T A Kuiken; G A Dumanian; R D Lipschutz; L A Miller; K A Stubblefield
Journal:  Prosthet Orthot Int       Date:  2004-12       Impact factor: 1.895

4.  Simulation of intramuscular EMG signals detected using implantable myoelectric sensors (IMES).

Authors:  Madeleine M Lowery; Richard F ff Weir; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2006-10       Impact factor: 4.538

Review 5.  Upper limb prosthesis use and abandonment: a survey of the last 25 years.

Authors:  Elaine A Biddiss; Tom T Chau
Journal:  Prosthet Orthot Int       Date:  2007-09       Impact factor: 1.895

6.  Assessment of capacity for myoelectric control: evaluation of construct and rating scale.

Authors:  Helen Y N Lindner; John M Linacre; Liselotte M Norling Hermansson
Journal:  J Rehabil Med       Date:  2009-05       Impact factor: 2.912

7.  Comparison of the Power Knee and C-Leg during step-up and sit-to-stand tasks.

Authors:  Erik J Wolf; Vanessa Q Everding; Alison A Linberg; Joseph M Czerniecki; Jeffrey M Gambel
Journal:  Gait Posture       Date:  2013-01-30       Impact factor: 2.840

8.  Estimating the prevalence of limb loss in the United States: 2005 to 2050.

Authors:  Kathryn Ziegler-Graham; Ellen J MacKenzie; Patti L Ephraim; Thomas G Travison; Ron Brookmeyer
Journal:  Arch Phys Med Rehabil       Date:  2008-03       Impact factor: 3.966

9.  Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms.

Authors:  Todd A Kuiken; Guanglin Li; Blair A Lock; Robert D Lipschutz; Laura A Miller; Kathy A Stubblefield; Kevin B Englehart
Journal:  JAMA       Date:  2009-02-11       Impact factor: 56.272

10.  Implantable myoelectric sensors (IMESs) for intramuscular electromyogram recording.

Authors:  Richard F ff Weir; Phil R Troyk; Glen A DeMichele; Douglas A Kerns; Jack F Schorsch; Huub Maas
Journal:  IEEE Trans Biomed Eng       Date:  2009-01       Impact factor: 4.538

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  38 in total

1.  Novel postural control algorithm for control of multifunctional myoelectric prosthetic hands.

Authors:  Jacob L Segil; Richard F Weir
Journal:  J Rehabil Res Dev       Date:  2015

2.  Upper extremity prosthesis user perspectives on unmet needs and innovative technology.

Authors:  Heather L Benz; Laura Rose; Okan Olgac; Karen Kreutz; Anindita Saha; Eugene F Civillico
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2016-08

Review 3.  [Prosthetic reconstruction of the upper extremity].

Authors:  S Salminger; J A Mayer; A Sturma; O Riedl; K D Bergmeister; O C Aszmann
Journal:  Unfallchirurg       Date:  2016-05       Impact factor: 1.000

4.  Motor unit drive: a neural interface for real-time upper limb prosthetic control.

Authors:  Michael D Twardowski; Serge H Roy; Zhi Li; Paola Contessa; Gianluca De Luca; Joshua C Kline
Journal:  J Neural Eng       Date:  2018-10-24       Impact factor: 5.379

5.  Myoelectric Control System and Task-Specific Characteristics Affect Voluntary Use of Simultaneous Control.

Authors:  Lauren H Smith; Todd A Kuiken; Levi J Hargrove
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-03-06       Impact factor: 3.802

6.  Use of probabilistic weights to enhance linear regression myoelectric control.

Authors:  Lauren H Smith; Todd A Kuiken; Levi J Hargrove
Journal:  J Neural Eng       Date:  2015-11-23       Impact factor: 5.379

Review 7.  The Evolution of Neuroprosthetic Interfaces.

Authors:  Dayo O Adewole; Mijail D Serruya; James P Harris; Justin C Burrell; Dmitriy Petrov; H Isaac Chen; John A Wolf; D Kacy Cullen
Journal:  Crit Rev Biomed Eng       Date:  2016

8.  Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

Authors:  Lauren H Smith; Todd A Kuiken; Levi J Hargrove
Journal:  IEEE Trans Biomed Eng       Date:  2015-08-20       Impact factor: 4.538

9.  An Alternative Myoelectric Pattern Recognition Approach for the Control of Hand Prostheses: A Case Study of Use in Daily Life by a Dysmelia Subject.

Authors:  Enzo Mastinu; Johan Ahlberg; Eva Lendaro; Liselotte Hermansson; Bo Hakansson; Max Ortiz-Catalan
Journal:  IEEE J Transl Eng Health Med       Date:  2018-03-12       Impact factor: 3.316

Review 10.  The future of upper extremity rehabilitation robotics: research and practice.

Authors:  Philip P Vu; Cynthia A Chestek; Samuel R Nason; Theodore A Kung; Stephen W P Kemp; Paul S Cederna
Journal:  Muscle Nerve       Date:  2020-06       Impact factor: 3.217

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