2A1-I02 Development of Musculoskeletal Gait Simulator with Real Foot Model based on CT-scanned human foot(Mobiligence and Embodiment)

2013 ◽  
Vol 2013 (0) ◽  
pp. _2A1-I02_1-_2A1-I02_4
Author(s):  
Shinnosuke KUME ◽  
Kenichi NARIOKA ◽  
Koh HOSODA ◽  
Naomichi OGIHARA ◽  
Masahiro JINZAKI ◽  
...  
Keyword(s):  
2013 ◽  
Vol 37 (1) ◽  
pp. 121-125 ◽  
Author(s):  
Prabhav Saraswat ◽  
Bruce A. MacWilliams ◽  
Roy B. Davis ◽  
Jacques L. D’Astous

2016 ◽  
Vol 147 ◽  
pp. 240-245 ◽  
Author(s):  
Zahari Taha ◽  
Muhammad Syukur Norman ◽  
Syed Faris Syed Omar ◽  
Edin Suwarganda

2020 ◽  
Vol 224 (1) ◽  
pp. jeb219667
Author(s):  
Nicholas B. Holowka ◽  
Alexander Richards ◽  
Benjamin E. Sibson ◽  
Daniel E. Lieberman

ABSTRACTLike other animals, humans use their legs like springs to save energy during running. One potential contributor to leg stiffness in humans is the longitudinal arch (LA) of the foot. Studies of cadaveric feet have demonstrated that the LA can function like a spring, but it is unknown whether humans can adjust LA stiffness in coordination with more proximal joints to help control leg stiffness during running. Here, we used 3D motion capture to record 27 adult participants running on a forceplate-instrumented treadmill, and calculated LA stiffness using beam bending and midfoot kinematics models of the foot. Because changing stride frequency causes humans to adjust overall leg stiffness, we had participants run at their preferred frequency and frequencies 35% above and 20% below preferred frequency to test for similar adjustments in the LA. Regardless of which foot model we used, we found that participants increased LA quasi-stiffness significantly between low and high frequency runs, mirroring changes at the ankle, knee and leg overall. However, among foot models, we found that the model incorporating triceps surae force into bending force on the foot produced unrealistically high LA work estimates, leading us to discourage this modeling approach. Additionally, we found that there was not a consistent correlation between LA height and quasi-stiffness values among the participants, indicating that static LA height measurements are not good predictors of dynamic function. Overall, our findings support the hypothesis that humans dynamically adjust LA stiffness during running in concert with other structures of the leg.


Author(s):  
Hikaru SUZUKI ◽  
Ryuji SUGIURA ◽  
Tetsuya NISHIMOTO ◽  
Rie NISHIKATA ◽  
Tatsuo FUJIKAWA

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.


2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.


Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery

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