Jason Friedman's literature database -- Query Results

Liebermann, D. G. (2008). Biomechanical aspects of motor control in human landing. In R. Bartlett, & Y. Hong (Eds.), Routledge Handbook of Biomechanics and Human Movement Science. Routledge Ltd. https://refbase.nfshost.com/show.php?record=47
Flash, T., Richardson, M. E., Handzel, A. A., & Liebermann, D. G. (2003). Computational Models and Geometric Approaches in Arm Trajectory Control Studies. In M. L. Latash, & M. F. Levin (Eds.), Progress in Motor Control III: From Basic Science to Applications. Champaign, Il: Human Kinetics. https://refbase.nfshost.com/show.php?record=44
Grip, H., Tengman, E., Liebermann, D. G., & Hager, C. K. (2019). Kinematic analyses including finite helical axes of drop jump landings demonstrate decreased knee control long after anterior cruciate ligament injury. PLoS One, 14(10), e0224261. Abstract: The purpose was to evaluate the dynamic knee control during a drop jump test following injury of the anterior cruciate ligament injury (ACL) using finite helical axes. Persons injured 17-28 years ago, treated with either physiotherapy (ACLPT, n = 23) or reconstruction and physiotherapy (ACLR, n = 28) and asymptomatic controls (CTRL, n = 22) performed a drop jump test, while kinematics were registered by motion capture. We analysed the Preparation phase (from maximal knee extension during flight until 50 ms post-touchdown) followed by an Action phase (until maximal knee flexion post-touchdown). Range of knee motion (RoM), and the length of each phase (Duration) were computed. The finite knee helical axis was analysed for momentary intervals of ~15 degrees of knee motion by its intersection (DeltaAP position) and inclination (DeltaAP Inclination) with the knee's Anterior-Posterior (AP) axis. Static knee laxity (KT100) and self-reported knee function (Lysholm score) were also assessed. The results showed that both phases were shorter for the ACL groups compared to controls (CTRL-ACLR: Duration 35+/-8 ms, p = 0.000, CTRL-ACLPT: 33+/-9 ms, p = 0.000) and involved less knee flexion (CTRL-ACLR: RoM 6.6+/-1.9 degrees , p = 0.002, CTRL-ACLR: 7.5 +/-2.0 degrees , p = 0.001). Low RoM and Duration correlated significantly with worse knee function according to Lysholm and higher knee laxity according to KT-1000. Three finite helical axes were analysed. The DeltaAP position for the first axis was most anterior in ACLPT compared to ACLR (DeltaAP position -1, ACLPT-ACLR: 13+/-3 mm, p = 0.004), with correlations to KT-1000 (rho 0.316, p = 0.008), while the DeltaAP inclination for the third axis was smaller in the ACLPT group compared to controls (DeltaAP inclination -3 ACLPT-CTRL: -13+/-5 degrees , p = 0.004) and showed a significant side difference in ACL injured groups during Action (Injured-Non-injured: 8+/-2.7 degrees , p = 0.006). Small DeltaAP inclination -3 correlated with low Lysholm (rho 0.391, p = 0.002) and high KT-1000 (rho -0.450, p = 0.001). Conclusions Compensatory movement strategies seem to be used to protect the injured knee during landing. A decreased DeltaAP inclination in injured knees during Action suggests that the dynamic knee control may remain compromised even long after injury. https://refbase.nfshost.com/show.php?record=102
Biess, A., Flash, T., & Liebermann, D. G. (2011). Riemannian geometric approach to human arm dynamics, movement optimization, and invariance. Phys Rev E Stat Nonlin Soft Matter Phys, 83(3 Pt 1), 031927. Abstract: We present a generally covariant formulation of human arm dynamics and optimization principles in Riemannian configuration space. We extend the one-parameter family of mean-squared-derivative (MSD) cost functionals from Euclidean to Riemannian space, and we show that they are mathematically identical to the corresponding dynamic costs when formulated in a Riemannian space equipped with the kinetic energy metric. In particular, we derive the equivalence of the minimum-jerk and minimum-torque change models in this metric space. Solutions of the one-parameter family of MSD variational problems in Riemannian space are given by (reparameterized) geodesic paths, which correspond to movements with least muscular effort. Finally, movement invariants are derived from symmetries of the Riemannian manifold. We argue that the geometrical structure imposed on the arm's configuration space may provide insights into the emerging properties of the movements generated by the motor system. Keywords: Arm/physiology; Biomechanics; Computer Simulation; Humans; Kinetics; Male; Models, Biological; Models, Statistical; Models, Theoretical; Movement; Psychomotor Performance/physiology; Range of Motion, Articular/physiology; Reaction Time/physiology; Space Perception/physiology; Torque https://refbase.nfshost.com/show.php?record=29
Liebermann, D. G., & Franks, I. M. (2004). The use of feedback-based technologies in skill acquisition. In M. Hughes, & I.M. Franks (Eds.), Notational analysis of Sport and Coaching Science. E & FN Spon Pub. https://refbase.nfshost.com/show.php?record=45

Liebermann, D. G. (2008). Biomechanical aspects of motor control in human landing. In R. Bartlett, & Y. Hong (Eds.), Routledge Handbook of Biomechanics and Human Movement Science. Routledge Ltd.

Flash, T., Richardson, M. E., Handzel, A. A., & Liebermann, D. G. (2003). Computational Models and Geometric Approaches in Arm Trajectory Control Studies. In M. L. Latash, & M. F. Levin (Eds.), Progress in Motor Control III: From Basic Science to Applications. Champaign, Il: Human Kinetics.

Grip, H., Tengman, E., Liebermann, D. G., & Hager, C. K. (2019). Kinematic analyses including finite helical axes of drop jump landings demonstrate decreased knee control long after anterior cruciate ligament injury. PLoS One, 14(10), e0224261.

Abstract: The purpose was to evaluate the dynamic knee control during a drop jump test following injury of the anterior cruciate ligament injury (ACL) using finite helical axes. Persons injured 17-28 years ago, treated with either physiotherapy (ACLPT, n = 23) or reconstruction and physiotherapy (ACLR, n = 28) and asymptomatic controls (CTRL, n = 22) performed a drop jump test, while kinematics were registered by motion capture. We analysed the Preparation phase (from maximal knee extension during flight until 50 ms post-touchdown) followed by an Action phase (until maximal knee flexion post-touchdown). Range of knee motion (RoM), and the length of each phase (Duration) were computed. The finite knee helical axis was analysed for momentary intervals of ~15 degrees of knee motion by its intersection (DeltaAP position) and inclination (DeltaAP Inclination) with the knee's Anterior-Posterior (AP) axis. Static knee laxity (KT100) and self-reported knee function (Lysholm score) were also assessed. The results showed that both phases were shorter for the ACL groups compared to controls (CTRL-ACLR: Duration 35+/-8 ms, p = 0.000, CTRL-ACLPT: 33+/-9 ms, p = 0.000) and involved less knee flexion (CTRL-ACLR: RoM 6.6+/-1.9 degrees , p = 0.002, CTRL-ACLR: 7.5 +/-2.0 degrees , p = 0.001). Low RoM and Duration correlated significantly with worse knee function according to Lysholm and higher knee laxity according to KT-1000. Three finite helical axes were analysed. The DeltaAP position for the first axis was most anterior in ACLPT compared to ACLR (DeltaAP position -1, ACLPT-ACLR: 13+/-3 mm, p = 0.004), with correlations to KT-1000 (rho 0.316, p = 0.008), while the DeltaAP inclination for the third axis was smaller in the ACLPT group compared to controls (DeltaAP inclination -3 ACLPT-CTRL: -13+/-5 degrees , p = 0.004) and showed a significant side difference in ACL injured groups during Action (Injured-Non-injured: 8+/-2.7 degrees , p = 0.006). Small DeltaAP inclination -3 correlated with low Lysholm (rho 0.391, p = 0.002) and high KT-1000 (rho -0.450, p = 0.001). Conclusions Compensatory movement strategies seem to be used to protect the injured knee during landing. A decreased DeltaAP inclination in injured knees during Action suggests that the dynamic knee control may remain compromised even long after injury.

https://refbase.nfshost.com/show.php?record=102

Biess, A., Flash, T., & Liebermann, D. G. (2011). Riemannian geometric approach to human arm dynamics, movement optimization, and invariance. Phys Rev E Stat Nonlin Soft Matter Phys, 83(3 Pt 1), 031927.

Liebermann, D. G., & Franks, I. M. (2004). The use of feedback-based technologies in skill acquisition. In M. Hughes, & I.M. Franks (Eds.), Notational analysis of Sport and Coaching Science. E & FN Spon Pub.