{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T07:07:40Z","timestamp":1760080060732,"version":"3.41.2"},"reference-count":46,"publisher":"ASME International","issue":"9","content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,9,1]]},"abstract":"<jats:p>Computational models of diarthrodial joints serve to inform the biomechanical function of these structures, and as such, must be supplied appropriate inputs for performance that is representative of actual joint function. Inputs for these models are sourced from both imaging modalities as well as literature. The latter is often the source of mechanical properties for soft tissues, like ligament stiffnesses; however, such data are not always available for all the soft tissues nor is it known for patient-specific work. In the current research, a method to improve the ligament stiffness definition for a computational foot\/ankle model was sought with the greater goal of improving the predictive ability of the computational model. Specifically, the stiffness values were optimized using artificial neural networks (ANNs); both feedforward and radial basis function networks (RBFNs) were considered. Optimal networks of each type were determined and subsequently used to predict stiffnesses for the foot\/ankle model. Ultimately, the predicted stiffnesses were considered reasonable and resulted in enhanced performance of the computational model, suggesting that artificial neural networks can be used to optimize stiffness inputs.<\/jats:p>","DOI":"10.1115\/1.4037101","type":"journal-article","created":{"date-parts":[[2017,6,20]],"date-time":"2017-06-20T22:31:03Z","timestamp":1497997863000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":1,"title":["Neural Network Optimization of Ligament Stiffnesses for the Enhanced Predictive Ability of a Patient-Specific, Computational Foot\/Ankle Model"],"prefix":"10.1115","volume":"139","author":[{"given":"Ruchi D.","family":"Chande","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Virginia Commonwealth University, 401 West Main Street, PO Box 843067, Richmond, VA 23284-3067"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer S.","family":"Wayne","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Virginia Commonwealth University, 401 West Main Street, PO Box 843067, Richmond, VA 23284-3067 e-mail:"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"33","published-online":{"date-parts":[[2017,7,7]]},"reference":[{"issue":"6","key":"2019100602231513800_bib1","doi-asserted-by":"publisher","first-page":"811","DOI":"10.1115\/1.2800763","article-title":"Computational Modeling to Predict Function of Joints: Application to the Lower Leg With Simulation of Two Cadaver Studies","volume":"129","year":"2007","journal-title":"ASME J. Biomech. Eng."},{"issue":"12","key":"2019100602231513800_bib2","doi-asserted-by":"publisher","first-page":"1861","DOI":"10.1002\/jor.22471","article-title":"Validation of a Population of Patient-Specific Adult Acquired Flatfoot Deformity Models","volume":"31","year":"2013","journal-title":"J. Orthop. Res."},{"issue":"6","key":"2019100602231513800_bib3","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1016\/j.bspc.2013.04.004","article-title":"Application of Neural Networks for the Prediction of Cartilage Stress in a Musculoskeletal System","volume":"8","year":"2013","journal-title":"Biomed. Signal Process. Control"},{"issue":"7","key":"2019100602231513800_bib4","doi-asserted-by":"publisher","first-page":"1047","DOI":"10.1002\/jor.21379","article-title":"Effects of Surgical Correction for the Treatment of Adult Acquired Flatfoot Deformity: A Computational Investigation","volume":"29","year":"2011","journal-title":"J. Orthop. Res."},{"issue":"5","key":"2019100602231513800_bib5","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1016\/j.jbiomech.2004.05.035","article-title":"Three-Dimensional Finite Element Analysis of the Foot During Standing\u2014A Material Sensitivity Study","volume":"38","year":"2005","journal-title":"J. Biomech."},{"issue":"2\u20133","key":"2019100602231513800_bib6","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1007\/s10237-006-0025-2","article-title":"Intra-Articular Contact Stress Distributions at the Ankle Throughout Stance Phase-Patient-Specific Finite Element Analysis as a Metric of Degeneration Propensity","volume":"5","year":"2006","journal-title":"Biomech. Model. Mechanobiol."},{"issue":"1","key":"2019100602231513800_bib7","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1243\/09544119JEIM156","article-title":"Finite Element Analysis of a Subtrochanteric Fractured Femur With Dynamic Hip Screw, Dynamic Condylar Screw, and Proximal Femur Nail Implants\u2014A Comparative Study","volume":"222","year":"2008","journal-title":"Proc. Inst. Mech. Eng. Part H"},{"issue":"3","key":"2019100602231513800_bib8","doi-asserted-by":"publisher","first-page":"1084","DOI":"10.1007\/s10439-010-0224-y","article-title":"Computational Model of the Human Elbow and Forearm: Application to Complex Varus Instability","volume":"39","year":"2011","journal-title":"Ann. Biomed. Eng."},{"issue":"11","key":"2019100602231513800_bib9","doi-asserted-by":"publisher","first-page":"2807","DOI":"10.1007\/s10439-011-0361-y","article-title":"Development and Validation of a Computational Model for Investigation of Wrist Biomechanics","volume":"39","year":"2011","journal-title":"Ann. Biomed. Eng."},{"issue":"7","key":"2019100602231513800_bib10","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1080\/10255842.2011.641120","article-title":"Soft Tissue Structures Resisting Anterior Instability in a Computational Glenohumeral Joint Model","volume":"16","year":"2013","journal-title":"Comput. Methods Biomech. Biomed. Eng."},{"issue":"7","key":"2019100602231513800_bib11","doi-asserted-by":"publisher","first-page":"399","DOI":"10.5435\/00124635-200807000-00005","article-title":"Adult-Acquired Flatfoot Deformity","volume":"16","year":"2008","journal-title":"J. Am. Acad. Orthop. Surg."},{"issue":"3","key":"2019100602231513800_bib12","doi-asserted-by":"publisher","first-page":"239","DOI":"10.3113\/FAI.2012.0239","article-title":"Spring Ligament Complex and Flatfoot Deformity: Curse or Blessing?","volume":"33","year":"2012","journal-title":"Foot Ankle Int."},{"issue":"7","key":"2019100602231513800_bib13","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1007\/s00256-013-1618-3","article-title":"MRI Features Most Often Associated With Surgically Proven Tears of the Spring Ligament Complex","volume":"42","year":"2013","journal-title":"Skeletal Radiol."},{"issue":"4","key":"2019100602231513800_bib14","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1007\/s12178-013-9173-z","article-title":"Approach and Treatment of the Adult Acquired Flatfoot Deformity","volume":"6","year":"2013","journal-title":"Curr. Rev. Musculoskeletal Med."},{"issue":"6","key":"2019100602231513800_bib15","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1177\/107110070502600601","article-title":"Posterior Tibial Tendon Insufficiency: Which Ligaments Are Involved?","volume":"26","year":"2005","journal-title":"Foot Ankle Int."},{"issue":"10","key":"2019100602231513800_bib16","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1177\/107110070502601006","article-title":"Radiographic Assessment of Adult Flatfoot","volume":"26","year":"2005","journal-title":"Foot Ankle Int."},{"issue":"7","key":"2019100602231513800_bib17","doi-asserted-by":"publisher","first-page":"958","DOI":"10.1002\/jor.22612","article-title":"Talonavicular Joint Coverage and Bone Morphology Between Different Foot Types","volume":"32","year":"2014","journal-title":"J. Orthop. Res."},{"issue":"8","key":"2019100602231513800_bib18","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1177\/1071100715576918","article-title":"Optimal Position of the Heel Following Reconstruction of the Stage II Adult-Acquired Flatfoot Deformity","volume":"36","year":"2015","journal-title":"Foot Ankle Int."},{"volume-title":"Anatomy of the Lower Extremity","year":"1986","key":"2019100602231513800_bib19"},{"issue":"8","key":"2019100602231513800_bib20","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1177\/107110070602700813","article-title":"Radiographic Comparison of Standing Medial Cuneiform Arch Height in Adults With and Without Acquired Flatfoot Deformity","volume":"27","year":"2006","journal-title":"Foot Ankle Int."},{"issue":"8","key":"2019100602231513800_bib21","doi-asserted-by":"publisher","first-page":"1947","DOI":"10.1007\/s10439-014-1195-1","article-title":"Effects of Degrees of Surgical Correction for Flatfoot Deformity in Patient-Specific Computational Models","volume":"43","year":"2015","journal-title":"Ann. Biomed. Eng."},{"journal-title":"Ph.D. thesis","article-title":"Patient-Specific Modeling of Adult Acquired Flatfoot Deformity Before and After Surgery","year":"2013","key":"2019100602231513800_bib22"},{"volume-title":"Fundamentals of Artificial Neural Networks","year":"1995","key":"2019100602231513800_bib23"},{"volume-title":"Neural Networks and Learning Machines","year":"2009","key":"2019100602231513800_bib24"},{"issue":"6","key":"2019100602231513800_bib25","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1109\/72.97934","article-title":"A General Regression Neural Network","volume":"2","year":"1991","journal-title":"IEEE Trans. Neural Networks"},{"volume-title":"Intelligent Systems Modeling and Decision Support in Bioengineering","year":"2006","key":"2019100602231513800_bib26"},{"volume-title":"Neural Networks Theory","year":"2007","key":"2019100602231513800_bib27"},{"issue":"5","key":"2019100602231513800_bib28","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1016\/S0731-7085(99)00272-1","article-title":"Basic Concepts of Artificial Neural Network (ANN) Modeling and Its Application in Pharmaceutical Research","volume":"22","year":"2000","journal-title":"J. Pharm. Biomed. Anal."},{"issue":"1","key":"2019100602231513800_bib29","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.joms.2011.03.069","article-title":"Use of Artificial Neural Network in Differentiation of Subgroups of Temporomandibular Internal Derangements: A Preliminary Study","volume":"70","year":"2012","journal-title":"J. Oral Maxillofac. Surg."},{"key":"2019100602231513800_bib30","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.jssas.2013.01.002","article-title":"Application of Artificial Neural Networks for the Prediction of Traction Performance Parameters","volume":"13","year":"2014","journal-title":"J. Saudi Soc. Agric. Sci."},{"issue":"1","key":"2019100602231513800_bib31","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/S0167-7012(00)00201-3","article-title":"Artificial Neural Networks: Fundamentals, Computing, Design, and Application","volume":"43","year":"2000","journal-title":"J. Microbiol. Methods"},{"article-title":"Neural Network Fundamentals for Scientists and Engineers","volume-title":"ECOS","year":"2001","key":"2019100602231513800_bib32"},{"issue":"1","key":"2019100602231513800_bib33","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1186\/1476-4598-4-29","article-title":"Artificial Neural Networks for Diagnosis and Survival Prediction in Colon Cancer","volume":"4","year":"2005","journal-title":"Mol. Cancer"},{"key":"2019100602231513800_bib34","doi-asserted-by":"publisher","DOI":"10.1115\/SBC2013-14581","article-title":"Surrogate Knee Contact Modeling Using Artificial Neural Networks","volume-title":"ASME","year":"2013"},{"issue":"3","key":"2019100602231513800_bib35","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1109\/51.59209","article-title":"A Neural Network Approach for Bone Fracture Healing Assessment","volume":"9","year":"1990","journal-title":"IEEE Eng. Med. Biol. Mag."},{"issue":"3","key":"2019100602231513800_bib36","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1177\/014107689909200305","article-title":"Artificial Neural Networks: A Potential Role in Osteoporosis","volume":"92","year":"1999","journal-title":"J. R. Soc. Med."},{"key":"2019100602231513800_bib37","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1145\/44571.44572","article-title":"An Introduction to Computing With Neural Nets","volume":"3","year":"1987","journal-title":"IEEE ASSP Mag."},{"year":"2015","key":"2019100602231513800_bib38","article-title":"Backpropagation: How It Works"},{"year":"2015","key":"2019100602231513800_bib39","article-title":"Neural Networks 11: Backpropagation in Detail"},{"year":"2012","key":"2019100602231513800_bib40","article-title":"Lecture 16: Radial Basis Functions"},{"year":"2013","key":"2019100602231513800_bib41","article-title":"Neural Network Toolbox\u2122, User's Guide R2013b"},{"article-title":"Improving the Performance of Radial Basis Function Networks by Learning Center Locations","volume-title":"Advances in Neural Information Processing Systems 4","year":"1992","key":"2019100602231513800_bib42"},{"volume-title":"Assessing and Improving Prediction and Classification","year":"2013","key":"2019100602231513800_bib43"},{"year":"2016","key":"2019100602231513800_bib44","article-title":"Tutorial on Neural Net Crossvalidation Design"},{"volume-title":"Anatomy of the Foot and Ankle: Descriptive, Topographic, Functional","year":"1993","key":"2019100602231513800_bib45"},{"issue":"3","key":"2019100602231513800_bib46","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1002\/jor.23032","article-title":"Estimating Patient-Specific Soft-Tissue Properties in a TKA Knee","volume":"34","year":"2016","journal-title":"J. Orthop. Res."}],"container-title":["Journal of Biomechanical Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/asmedigitalcollection.asme.org\/biomechanical\/article-pdf\/doi\/10.1115\/1.4037101\/6095391\/bio_139_09_091003.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/asmedigitalcollection.asme.org\/biomechanical\/article-pdf\/doi\/10.1115\/1.4037101\/6095391\/bio_139_09_091003.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,6]],"date-time":"2019-10-06T06:23:25Z","timestamp":1570343005000},"score":1,"resource":{"primary":{"URL":"https:\/\/asmedigitalcollection.asme.org\/biomechanical\/article\/doi\/10.1115\/1.4037101\/371074\/Neural-Network-Optimization-of-Ligament"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,7]]},"references-count":46,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2017,9,1]]}},"URL":"https:\/\/doi.org\/10.1115\/1.4037101","relation":{},"ISSN":["0148-0731","1528-8951"],"issn-type":[{"type":"print","value":"0148-0731"},{"type":"electronic","value":"1528-8951"}],"subject":[],"published":{"date-parts":[[2017,7,7]]},"article-number":"091003"}}