McKenna C Everett, Wentao Li, Ann Majewicz Fey, Nicholas P Fey
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引用次数: 0
Abstract
Observational gait analysis and categorical ratings are commonly used by clinicians to assess pathologies. The purpose of this study was to determine the capacity of novice observers to characterize the gait behavior underlying biomechanical performance objectives using stylistic labels. We hypothesized that visual characterization of physics-based musculoskeletal predictive simulations of walking would be sensitive to the biomechanical objective employed by individuals, as well as the visual perspective. We developed 75 full-body muscle-driven predictive gait simulation videos, corresponding to five subject models, five biomechanical objectives, and three visual perspectives. Subject models were constructed for five individuals performing straight line walking, with optimal tracking simulations generated for each using computed muscle control. Direct collocation was used to apply five different objectives to each individual's nominal behavior including metabolic cost, summed and squared muscle activations, time-integrated whole-body angular momentum, time-integrated bilateral ground reaction forces, and an equally weighted multi-objective cost function summing the individual objectives. 100 crowd workers characterized each simulation on a 1-5 scale using stylistic labels corresponding to each objective. Multinomial logistic regression analysis revealed that loading and activation ratings were significant predictors of muscle activation-optimized movements, while activation ratings were significant predictors of movement perspective. Balance ratings were significant for the frontal view alone, suggesting that balance indicators are more easily distinguished in the frontal plane. Collectively, the wisdom of crowds could distinguish motion associated with some biomechanical objectives, but due to the redundancy of motor control strategies used by individuals, the resolution of this observational approach is limited.