Classical and adaptive control of ex vivo skeletal muscle contractions using Functional Electrical Stimulation (FES)

Simple item page
dc.contributor.authorCienfuegos, Paola Jaramilloen
dc.contributor.authorShoemaker, Adamen
dc.contributor.authorGrange, Robert W.en
dc.contributor.authorAbaid, Nicoleen
dc.contributor.authorLeonessa, Alexanderen
dc.contributor.departmentMechanical Engineeringen
dc.contributor.departmentBiomedical Engineering and Mechanicsen
dc.contributor.departmentHuman Nutrition, Foods, and Exerciseen
dc.date.accessioned2017-07-14T19:38:01Zen
dc.date.available2017-07-14T19:38:01Zen
dc.date.issued2017-03-08en
dc.description.abstractFunctional Electrical Stimulation is a promising approach to treat patients by stimulating the peripheral nerves and their corresponding motor neurons using electrical current. This technique helps maintain muscle mass and promote blood flow in the absence of a functioning nervous system. The goal of this work is to control muscle contractions from FES via three different algorithms and assess the most appropriate controller providing effective stimulation of the muscle. An open-loop system and a closed-loop system with three types of model-free feedback controllers were assessed for tracking control of skeletal muscle contractions: a Proportional-Integral (PI) controller, a Model Reference Adaptive Control algorithm, and an Adaptive Augmented PI system. Furthermore, a mathematical model of a muscle-mass-spring system was implemented in simulation to test the open-loop case and closed-loop controllers. These simulations were carried out and then validated through experiments ex vivo. The experiments included muscle contractions following four distinct trajectories: a step, sine, ramp, and square wave. Overall, the closed-loop controllers followed the stimulation trajectories set for all the simulated and tested muscles. When comparing the experimental outcomes of each controller, we concluded that the Adaptive Augmented PI algorithm provided the best closed-loop performance for speed of convergence and disturbance rejection.en
dc.description.versionPublished versionen
dc.format.extent? - ? (29) page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0172761en
dc.identifier.issn1932-6203en
dc.identifier.issue3en
dc.identifier.orcidAbaid, N [0000-0002-0053-4710]en
dc.identifier.urihttp://hdl.handle.net/10919/78341en
dc.identifier.volume12en
dc.language.isoenen
dc.publisherPLOSen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000396073700029&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsCreative Commons CC0 1.0 Universal Public Domain Dedicationen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.subjectneural-network controlen
dc.subjectneuromuscular stimulationen
dc.subjectrat musclesen
dc.subjectmodelen
dc.subjectsimulationen
dc.subjectfrequencyen
dc.subjectpatternsen
dc.subjectfatigueen
dc.titleClassical and adaptive control of ex vivo skeletal muscle contractions using Functional Electrical Stimulation (FES)en
dc.title.serialPLOS ONEen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciencesen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciences/CALS T&R Facultyen
pubs.organisational-group/Virginia Tech/Agriculture & Life Sciences/Human Nutrition, Foods, & Exerciseen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Biomedical Engineering and Mechanicsen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/Mechanical Engineeringen
pubs.organisational-group/Virginia Tech/Faculty of Health Sciencesen
pubs.organisational-group/Virginia Tech/University Research Institutesen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciencesen
pubs.organisational-group/Virginia Tech/University Research Institutes/Fralin Life Sciences/Fralin Affiliated Facultyen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Classical and adaptive control of ex vivo skeletal muscle contractions using Functional Electrical Stimulation (FES).pdf
Size:
3.88 MB
Format:
Adobe Portable Document Format
Description:
Publisher's Version
Download
License bundle
Now showing 1 - 1 of 1
Name:
VTUL_Distribution_License_2016_05_09.pdf
Size:
18.09 KB
Format:
Adobe Portable Document Format
Description:
Download

Collections

All Faculty Deposits
Scholarly Works, Biomedical Engineering and Mechanics
Scholarly Works, Human Nutrition, Foods, and Exercise
Scholarly Works, Mechanical Engineering