Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait

Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the "Grand Challenge Competition to P...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of biomechanical engineering 2014-02, Vol.136 (2), p.021032-np
Hauptverfasser: Guess, Trent M, Stylianou, Antonis P, Kia, Mohammad
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page np
container_issue 2
container_start_page 021032
container_title Journal of biomechanical engineering
container_volume 136
creator Guess, Trent M
Stylianou, Antonis P
Kia, Mohammad
description Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the "Grand Challenge Competition to Predict in-vivo Knee Loads" for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, "Grand Challenge Competition to Predict in vivo Knee Loads," J. Orthop. Res., 30, pp. 503-513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cy
doi_str_mv 10.1115/1.4026359
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4023658</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1530954645</sourcerecordid><originalsourceid>FETCH-LOGICAL-a564t-b446e7ef68cb994c8cb7112ba006dbae65bcd473ba2b2260a9fbecb84474e58f3</originalsourceid><addsrcrecordid>eNqNkb1vFDEQxS1ERI5AQY2EXIZig8dfazdI6EICUiIoLrVle2eDo911sHeR-O_Z6I4IKqimmN88vTePkFfAzgBAvYMzybgWyj4hG1DcNMYqeEo2DKRpWCvgmDyv9Y4xACPZM3LMpTDW2nZDbrZ5ikspOM30a8EuxTnlieaeXi81Dkj91NFdCin3OObiB7oezD7O9CKXiJWeLyVNt3RX0HdjGgZ66dP8ghz1fqj48jBPyM3Fx932U3P15fLz9sNV45WWcxOk1Nhir00M1sq4jhaAB8-Y7oJHrULsZCuC54FzzbztA8ZgpGwlKtOLE_J-r3u_hBG7uKZYLbr7kkZffrrsk_t7M6Vv7jb_cOu_hFZmFTg9CJT8fcE6uzHViMPgJ8xLdaBbUFZbJv6NKsGsklqq_0A5E0ZI_qD6do_Gkmst2D-aB-YeynXgDuWu7Js_0z6Sv9tcgdd7wNcR3V1eyrR-30nJrQDxC_MuqHM</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1520383423</pqid></control><display><type>article</type><title>Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait</title><source>ASME Digital Collection Journals</source><source>MEDLINE</source><source>Alma/SFX Local Collection</source><creator>Guess, Trent M ; Stylianou, Antonis P ; Kia, Mohammad</creator><creatorcontrib>Guess, Trent M ; Stylianou, Antonis P ; Kia, Mohammad</creatorcontrib><description>Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the "Grand Challenge Competition to Predict in-vivo Knee Loads" for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, "Grand Challenge Competition to Predict in vivo Knee Loads," J. Orthop. Res., 30, pp. 503-513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cycle and 43 N, 15 N, and 96 N in the anterior-posterior, medial-lateral, and vertical directions for the second gait cycle.</description><identifier>ISSN: 0148-0731</identifier><identifier>EISSN: 1528-8951</identifier><identifier>DOI: 10.1115/1.4026359</identifier><identifier>PMID: 24389997</identifier><language>eng</language><publisher>United States: ASME</publisher><subject>Computer Simulation ; Constraints ; Contact ; Errors ; Exercise Test ; Female ; Femur - physiology ; Friction ; Gait ; Gait - physiology ; Humans ; Knee Joint - physiology ; Knees ; Loads (forces) ; Male ; Mathematical models ; Models, Biological ; Muscle Contraction - physiology ; Muscle, Skeletal - physiology ; Muscles ; Physical Exertion - physiology ; Research Papers ; Stress, Mechanical ; Tibia - physiology ; Young Adult</subject><ispartof>Journal of biomechanical engineering, 2014-02, Vol.136 (2), p.021032-np</ispartof><rights>Copyright © 2014 by ASME 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a564t-b446e7ef68cb994c8cb7112ba006dbae65bcd473ba2b2260a9fbecb84474e58f3</citedby><cites>FETCH-LOGICAL-a564t-b446e7ef68cb994c8cb7112ba006dbae65bcd473ba2b2260a9fbecb84474e58f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925,38520</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24389997$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guess, Trent M</creatorcontrib><creatorcontrib>Stylianou, Antonis P</creatorcontrib><creatorcontrib>Kia, Mohammad</creatorcontrib><title>Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait</title><title>Journal of biomechanical engineering</title><addtitle>J Biomech Eng</addtitle><addtitle>J Biomech Eng</addtitle><description>Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the "Grand Challenge Competition to Predict in-vivo Knee Loads" for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, "Grand Challenge Competition to Predict in vivo Knee Loads," J. Orthop. Res., 30, pp. 503-513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cycle and 43 N, 15 N, and 96 N in the anterior-posterior, medial-lateral, and vertical directions for the second gait cycle.</description><subject>Computer Simulation</subject><subject>Constraints</subject><subject>Contact</subject><subject>Errors</subject><subject>Exercise Test</subject><subject>Female</subject><subject>Femur - physiology</subject><subject>Friction</subject><subject>Gait</subject><subject>Gait - physiology</subject><subject>Humans</subject><subject>Knee Joint - physiology</subject><subject>Knees</subject><subject>Loads (forces)</subject><subject>Male</subject><subject>Mathematical models</subject><subject>Models, Biological</subject><subject>Muscle Contraction - physiology</subject><subject>Muscle, Skeletal - physiology</subject><subject>Muscles</subject><subject>Physical Exertion - physiology</subject><subject>Research Papers</subject><subject>Stress, Mechanical</subject><subject>Tibia - physiology</subject><subject>Young Adult</subject><issn>0148-0731</issn><issn>1528-8951</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkb1vFDEQxS1ERI5AQY2EXIZig8dfazdI6EICUiIoLrVle2eDo911sHeR-O_Z6I4IKqimmN88vTePkFfAzgBAvYMzybgWyj4hG1DcNMYqeEo2DKRpWCvgmDyv9Y4xACPZM3LMpTDW2nZDbrZ5ikspOM30a8EuxTnlieaeXi81Dkj91NFdCin3OObiB7oezD7O9CKXiJWeLyVNt3RX0HdjGgZ66dP8ghz1fqj48jBPyM3Fx932U3P15fLz9sNV45WWcxOk1Nhir00M1sq4jhaAB8-Y7oJHrULsZCuC54FzzbztA8ZgpGwlKtOLE_J-r3u_hBG7uKZYLbr7kkZffrrsk_t7M6Vv7jb_cOu_hFZmFTg9CJT8fcE6uzHViMPgJ8xLdaBbUFZbJv6NKsGsklqq_0A5E0ZI_qD6do_Gkmst2D-aB-YeynXgDuWu7Js_0z6Sv9tcgdd7wNcR3V1eyrR-30nJrQDxC_MuqHM</recordid><startdate>20140201</startdate><enddate>20140201</enddate><creator>Guess, Trent M</creator><creator>Stylianou, Antonis P</creator><creator>Kia, Mohammad</creator><general>ASME</general><general>American Society of Mechanical Engineers</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope><scope>7TB</scope><scope>7U5</scope><scope>F28</scope><scope>L7M</scope><scope>5PM</scope></search><sort><creationdate>20140201</creationdate><title>Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait</title><author>Guess, Trent M ; Stylianou, Antonis P ; Kia, Mohammad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a564t-b446e7ef68cb994c8cb7112ba006dbae65bcd473ba2b2260a9fbecb84474e58f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Computer Simulation</topic><topic>Constraints</topic><topic>Contact</topic><topic>Errors</topic><topic>Exercise Test</topic><topic>Female</topic><topic>Femur - physiology</topic><topic>Friction</topic><topic>Gait</topic><topic>Gait - physiology</topic><topic>Humans</topic><topic>Knee Joint - physiology</topic><topic>Knees</topic><topic>Loads (forces)</topic><topic>Male</topic><topic>Mathematical models</topic><topic>Models, Biological</topic><topic>Muscle Contraction - physiology</topic><topic>Muscle, Skeletal - physiology</topic><topic>Muscles</topic><topic>Physical Exertion - physiology</topic><topic>Research Papers</topic><topic>Stress, Mechanical</topic><topic>Tibia - physiology</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guess, Trent M</creatorcontrib><creatorcontrib>Stylianou, Antonis P</creatorcontrib><creatorcontrib>Kia, Mohammad</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of biomechanical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guess, Trent M</au><au>Stylianou, Antonis P</au><au>Kia, Mohammad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait</atitle><jtitle>Journal of biomechanical engineering</jtitle><stitle>J Biomech Eng</stitle><addtitle>J Biomech Eng</addtitle><date>2014-02-01</date><risdate>2014</risdate><volume>136</volume><issue>2</issue><spage>021032</spage><epage>np</epage><pages>021032-np</pages><issn>0148-0731</issn><eissn>1528-8951</eissn><abstract>Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the "Grand Challenge Competition to Predict in-vivo Knee Loads" for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, "Grand Challenge Competition to Predict in vivo Knee Loads," J. Orthop. Res., 30, pp. 503-513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cycle and 43 N, 15 N, and 96 N in the anterior-posterior, medial-lateral, and vertical directions for the second gait cycle.</abstract><cop>United States</cop><pub>ASME</pub><pmid>24389997</pmid><doi>10.1115/1.4026359</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0148-0731
ispartof Journal of biomechanical engineering, 2014-02, Vol.136 (2), p.021032-np
issn 0148-0731
1528-8951
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4023658
source ASME Digital Collection Journals; MEDLINE; Alma/SFX Local Collection
subjects Computer Simulation
Constraints
Contact
Errors
Exercise Test
Female
Femur - physiology
Friction
Gait
Gait - physiology
Humans
Knee Joint - physiology
Knees
Loads (forces)
Male
Mathematical models
Models, Biological
Muscle Contraction - physiology
Muscle, Skeletal - physiology
Muscles
Physical Exertion - physiology
Research Papers
Stress, Mechanical
Tibia - physiology
Young Adult
title Concurrent Prediction of Muscle and Tibiofemoral Contact Forces During Treadmill Gait
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T20%3A58%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Concurrent%20Prediction%20of%20Muscle%20and%20Tibiofemoral%20Contact%20Forces%20During%20Treadmill%20Gait&rft.jtitle=Journal%20of%20biomechanical%20engineering&rft.au=Guess,%20Trent%20M&rft.date=2014-02-01&rft.volume=136&rft.issue=2&rft.spage=021032&rft.epage=np&rft.pages=021032-np&rft.issn=0148-0731&rft.eissn=1528-8951&rft_id=info:doi/10.1115/1.4026359&rft_dat=%3Cproquest_pubme%3E1530954645%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1520383423&rft_id=info:pmid/24389997&rfr_iscdi=true