Literature DB >> 33441604

Clinical evaluation of the revolutionizing prosthetics modular prosthetic limb system for upper extremity amputees.

Kristin E Yu1, Briana N Perry2, Courtney W Moran3, Robert S Armiger3, Matthew S Johannes4, Abigail Hawkins5, Lauren Stentz2, Jamie Vandersea6, Jack W Tsao7,8, Paul F Pasquina5.   

Abstract

Individuals with upper extremity (UE) amputation abandon prostheses due to challenges with significant device weight-particularly among myoelectric prostheses-and limited device dexterity, durability, and reliability among both myoelectric and body-powered prostheses. The Modular Prosthetic Limb (MPL) system couples an advanced UE prosthesis with a pattern recognition paradigm for intuitive, non-invasive prosthetic control. Pattern recognition accuracy and functional assessment-Box & Blocks (BB), Jebsen-Taylor Hand Function Test (JHFT), and Assessment of Capacity for Myoelectric Control (ACMC)-scores comprised the main outcomes. 10 participants were included in analyses, including seven individuals with traumatic amputation, two individuals with congenital limb absence, and one with amputation secondary to malignancy. The average (SD) time since limb loss, excluding congenital participants, was 85.9 (59.5) months. Participants controlled an average of eight motion classes compared to three with their conventional prostheses. All participants made continuous improvements in motion classifier accuracy, pathway completion efficiency, and MPL manipulation. BB and JHFT improvements were not statistically significant. ACMC performance improved for all participants, with mean (SD) scores of 162.6 (105.3), 213.4 (196.2), and 383.2 (154.3), p = 0.02 between the baseline, midpoint, and exit assessments, respectively. Feedback included lengthening the training period to further improve motion classifier accuracy and MPL control. The MPL has potential to restore functionality to individuals with acquired or congenital UE loss.

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Mesh:

Year:  2021        PMID: 33441604      PMCID: PMC7806748          DOI: 10.1038/s41598-020-79581-8

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.996


  26 in total

Review 1.  Differences in myoelectric and body-powered upper-limb prostheses: Systematic literature review.

Authors:  Stephanie L Carey; Derek J Lura; M Jason Highsmith
Journal:  J Rehabil Res Dev       Date:  2015

Review 2.  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

3.  A real-time virtual integration environment for the design and development of neural prosthetic systems.

Authors:  William Bishop; Robert Armiger; James Burck; Michael Bridges; Markus Hauschild; Kevin Englehart; Erik Scheme; R Jacob Vogelstein; James Beaty; Stuart Harshbarger
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008

4.  A Retrospective Comparison of Five-Year Health Outcomes Following Upper Limb Amputation and Serious Upper Limb Injury in the Iraq and Afghanistan Conflicts.

Authors:  Ted Melcer; Jay Walker; Vernon Franklin Sechriest; Vibha Bhatnagar; Erin Richard; Katheryne Perez; Michael Galarneau
Journal:  PM R       Date:  2019-03-29       Impact factor: 2.298

5.  The McGill pain questionnaire: from description to measurement.

Authors:  Ronald Melzack
Journal:  Anesthesiology       Date:  2005-07       Impact factor: 7.892

6.  Principal components analysis based control of a multi-DoF underactuated prosthetic hand.

Authors:  Giulia C Matrone; Christian Cipriani; Emanuele L Secco; Giovanni Magenes; Maria Chiara Carrozza
Journal:  J Neuroeng Rehabil       Date:  2010-04-23       Impact factor: 4.262

7.  How should we use the visual analogue scale (VAS) in rehabilitation outcomes? II: Visual analogue scales as ratio scales: an alternative to the view of Kersten et al.

Authors:  Donald D Price; Roland Staud; Michael E Robinson
Journal:  J Rehabil Med       Date:  2012-09       Impact factor: 2.912

8.  Consumer design priorities for upper limb prosthetics.

Authors:  Elaine Biddiss; Dorcas Beaton; Tom Chau
Journal:  Disabil Rehabil Assist Technol       Date:  2007-11

9.  The Reality of Myoelectric Prostheses: Understanding What Makes These Devices Difficult for Some Users to Control.

Authors:  Alix Chadwell; Laurence Kenney; Sibylle Thies; Adam Galpin; John Head
Journal:  Front Neurorobot       Date:  2016-08-22       Impact factor: 2.650

10.  Myoelectric Pattern Recognition Outperforms Direct Control for Transhumeral Amputees with Targeted Muscle Reinnervation: A Randomized Clinical Trial.

Authors:  Levi J Hargrove; Laura A Miller; Kristi Turner; Todd A Kuiken
Journal:  Sci Rep       Date:  2017-10-23       Impact factor: 4.379

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