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( 3 ): 592 – 597 . PubMed ID: 16540850 doi:10.1249/01.mss.0000193560.34022.04 16540850 10.1249/01.mss.0000193560.34022.04 7. di Prampero PE , Cortili G , Mognoni P , Saibene F . Equation of motion of a cyclist . J Appl Physiol Respir Environ Exerc Physiol . 1979 ; 47 ( 1 ): 201 – 206

acceleration were exported from the manufacturer’s software and processed in a customized fashion (R, version 3.3.3; Foundation for Statistical Computing, Vienna, Austria), with distances calculated via an equation of motion. 23 GPS data were discarded, according to previous recommendations, 24 where the

maximized by increasing net vertical impulse generated. As vertical impulse increases during the takeoff, negative horizontal impulse tends to linearly increase as well. 10 – 12 An increase in CM vertical velocity achieved at departure can be shown using projectile equations of motion to be nearly twice as

associated with elite endurance cycling performance . Med Sci Sports Exerc . 1991 ; 23 ( 1 ): 93 – 107 . PubMed ID: 1997818 doi:10.1249/00005768-199101000-00015 1997818 10.1249/00005768-199101000-00015 4. di Prampero PE , Cortili G , Mognoni P , Saibene F . Equation of motion of a cyclist . J

insertion points, and wrapping points were based on Delp et al. 34 A kinematic solver determined skeletal model kinematics using global optimization. 35 Joint moments were then obtained from equations of motion and inverse dynamics within the Human Body Model. Muscle forces were determined from the joint

cut-off frequency of 8 Hz to avoid inconsistencies in the equations of motion as per processing methods recommendations. 27 A right-hand rule with a Cardan rotational sequence (x-y-z) was used for the 3D angular computations where x represents the medial-lateral axis, y represents the anterior

.34022.04 16540850 2. Froncioni A . Cycling science . In: Cheung SS , Zabala M , eds. Cycling Science: The Ultimate Nexus of Knowledge and Performance . 1st ed. Champaign, IL : Human Kinetics ; 2017 : 92 – 109 . 3. di Prampero PE , Cortili G , Mognoni P , Saibene F . Equation of motion of

, on the moon . Eur J Appl Physiol . 2000 ; 82 : 345 – 360 . PubMed doi:10.1007/s004210000220 10.1007/s004210000220 19. Di Prampero PE , Cortili G , Mognoni P , Saibene F . Equation of motion of a cyclist . J Appl Physiol . 1979 ; 47 : 201 – 206 . PubMed 10.1152/jappl.1979.47.1.201 20

equations of motion for the ball and fingers are expressed as follows: F ball + m ball g = m ball a ball , (5) F 1 − F ball + m 1 g = m 1 a g 1 , (6) T f 1 + ( − L g 1 ) × F 1 + l × F ball = I 1 ω ˙ 1 + ω 1 × ( I 1 ω 1 ) . (7) Combining these equations, the following equations are obtained: T f 1 =   I 1

researchers went further and built equations of motion from physical models to test in a developmental context. One example of this approach is a study on infants bouncing in a baby bouncer where the discovery of the ability to use the properties of the spring was described ( Goldfield, Kay, & Warren, 1993