{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T19:05:14Z","timestamp":1790622314521,"version":"4.1.0"},"reference-count":33,"publisher":"ASME International","issue":"3","content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[1998,6,1]]},"abstract":"<jats:p>The objectives of this study were twofold. The first was to develop a forward dynamic model of cycling and an optimization framework to simulate pedaling during submaximal steady-state cycling conditions. The second was to use the model and framework to identify the kinetic, kinematic, and muscle timing quantities that should be included in a performance criterion to reproduce natural pedaling mechanics best during these pedaling conditions. To make this identification, kinetic and kinematic data were collected from 6 subjects who pedaled at 90 rpm and 225 W. Intersegmental joint moments were computed using an inverse dynamics technique and the muscle excitation onset and offset were taken from electromyographic (EMG) data collected previously (Neptune et al., 1997). Average cycles and their standard deviations for the various quantities were used to describe normal pedaling mechanics. The model of the bicycle-rider system was driven by 15 muscle actuators per leg. The optimization framework determined both the timing and magnitude of the muscle excitations to simulate pedaling at 90 rpm and 225 W. Using the model and optimization framework, seven performance criteria were evaluated. The criterion that included all of the kinematic and kinetic quantities combined with the EMG timing was the most successful in replicating the experimental data. The close agreement between the simulation results and the experimentally collected kinetic, kinematic, and EMG data gives confidence in the model to investigate individual muscle coordination during submaximal steady-state pedaling conditions from a theoretical perspective, which to date has only been performed experimentally.<\/jats:p>","DOI":"10.1115\/1.2797999","type":"journal-article","created":{"date-parts":[[2008,2,21]],"date-time":"2008-02-21T20:37:32Z","timestamp":1203626252000},"page":"334-341","update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":116,"title":["Evaluation of Performance Criteria for Simulation of Submaximal Steady-State Cycling Using a Forward Dynamic Model"],"prefix":"10.1115","volume":"120","author":[{"given":"R. R.","family":"Neptune","sequence":"first","affiliation":[{"name":"Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. L.","family":"Hull","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, University of California, Davis, Davis, CA 95616"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"33","published-online":{"date-parts":[[1998,6,1]]},"reference":[{"key":"2019100603492907100_r1","doi-asserted-by":"crossref","unstructured":"Audu\n              M. L.\n            , and DavyD. T., 1985, \u201cThe influence of muscle model complexity in musculoskeletal motion modeling,\u201d ASME JOURNAL OF BIOMECHANICAL ENGINEERING, 107: 147\u2013157.","DOI":"10.1115\/1.3138535"},{"key":"2019100603492907100_r2","unstructured":"Bogert, A. J. v. d., and Soest, A. 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