Data from: Constructing predictive models of human running
Data files
Nov 19, 2015 version files 1.78 GB
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info.txt
3.65 KB
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markerpos.pdf
83.47 KB
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slip_parameter.zip
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subj1_r1.zip
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subj1_r2.zip
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subj1_r3.zip
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subj1_r4.zip
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subj1_r5.zip
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subj1_r6.zip
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subj2_r1.zip
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subj2_r2.zip
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subj2_r3.zip
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subj2_r4.zip
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subj2_r5.zip
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subj2_r6.zip
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subj3_r1.zip
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subj3_r2.zip
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subj3_r3.zip
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subj3_r4.zip
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subj3_r6.zip
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subj7_r1.zip
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subj7_r2.zip
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subj7_r3.zip
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subj7_r4.zip
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subj7_r5.zip
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subj7_r6.zip
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Abstract
Running is an essential mode of human locomotion, during which ballistic aerial phases alternate with phases when a single foot contacts the ground. The spring-loaded inverted pendulum (SLIP) provides a starting point for modelling running, and generates ground reaction forces that resemble those of the centre of mass (CoM) of a human runner. Here, we show that while SLIP reproduces within-step kinematics of the CoM in three dimensions, it fails to reproduce stability and predict future motions. We construct SLIP control models using data-driven Floquet analysis, and show how these models may be used to obtain predictive models of human running with six additional states comprising the position and velocity of the swing-leg ankle. Our methods are general, and may be applied to any rhythmic physical system. We provide an approach for identifying an event-driven linear controller that approximates an observed stabilization strategy, and for producing a reduced-state model which closely recovers the observed dynamics.