“…Second, we did not use three-dimensional (3D) motion capture system outdoors because of the non-optimal conditions of light for the use of infrared cameras, as well as the need to move our setup two times (from surface to surface) during an entire experiment. However, previous studies reported good agreement between 2D and 3D methods for lower body kinematics and kinetics during jumping ( Hickox et al, 2016 ). Since the CMJ task is mainly restrained to the sagittal plane, we assume that 2D high speed video is appropriate to appraise the influence of different surfaces on 2D joint kinematics ( Hickox et al, 2016 ).…”
Section: Discussionmentioning
confidence: 89%
“…However, previous studies reported good agreement between 2D and 3D methods for lower body kinematics and kinetics during jumping ( Hickox et al, 2016 ). Since the CMJ task is mainly restrained to the sagittal plane, we assume that 2D high speed video is appropriate to appraise the influence of different surfaces on 2D joint kinematics ( Hickox et al, 2016 ). Third, we used a simple foot model to capture ankle kinematics, which is then used to compute MTU length.…”
Section: Discussionmentioning
confidence: 89%
“…Since it was not possible to use a laboratory motion capture system outdoors, a high-speed video camera (300 frame.s –1 ; Casio Exilim EX-F1, Japan) was used to record the two-dimensional (2D) positions of six reflective markers placed on the right side of the participants at the following locations: the fifth metatarsal, lateral calcaneus, lateral malleolus, lateral femoral epicondyle, great trochanter, and the acromion. The camera axis was perpendicular to the sagittal plane of jumping to prevent from image distortion and inaccurate marker trajectories ( Kurokawa et al, 2003 ; Hickox et al, 2016 ). Marker trajectories were semi-automatically digitized (Dartfish ProSuite 9.0, Fribourg, Switzerland), low-pass filtered (8 Hz) ( Kurokawa et al, 2003 ) and used to retrieve marker coordinates.…”
Interactions between human movement and surfaces have previously been studied to understand the influence of surface properties on the mechanics and energetics of jumping. However, little is known about the muscle-tendon unit (MTU) mechanics associated with muscle activity and leg adjustments induced by different surfaces during this movement. This study aimed to examine the effects of three surfaces with different properties (artificial turf, hybrid turf, and athletic track) on the muscle mechanics and muscle excitation of the gastrocnemius medialis (GM) and vastus lateralis (VL) during maximal countermovement jumping (CMJ). Twelve participants performed maximal CMJs on the three sport surfaces. GM and VL muscle fascicles were simultaneously imaged using two ultrafast ultrasound systems (500 Hz). MTUs lengths were determined based on anthropometric models and two-dimensional joint kinematics. Surface electromyography (EMG) was used to record GM and VL muscle activity. Surface mechanical testing revealed systematic differences in surface mechanical properties (
P
= 0.006, η
2
: 0.26–0.32,
large
). Specifically, the highest force reduction and vertical deformation values have been observed on artificial turf (65 ± 2% and 9.0 ± 0.3 mm, respectively), while athletic track exhibited the lowest force reduction and vertical deformation values (28 ± 1% and 2.1 ± 0.1 mm, respectively) and the highest energy restitution (65 ± 1%). We observed no significant difference in CMJ performance between the three surfaces (∼35–36 cm,
P
= 0.66). GM and VL fascicle shortening (
P
= 0.90 and
P
= 0.94, respectively) and shortening velocity (
P
= 0.13 and
P
= 0.65, respectively) were also unaffected by the type of surface. However, when jumping from greater deformable surface, both GM muscle activity (
P
= 0.022, η
2
= 0.18,
large
) and peak shortening velocity of GM MTU (
P
= 0.042, η
2
= 0.10,
medium
) increased during the push-off phase. This resulted in a greater peak plantar flexion velocity late in the jump (
P
= 0.027, η
2
= 0.13,
medium
). Our findings suggest that maximal vertical jumping tasks in humans is not affected by common sport surfaces with different mechanical properties. However, internal regulatory mechanisms exist to compensate for differences in surface properties.
“…Second, we did not use three-dimensional (3D) motion capture system outdoors because of the non-optimal conditions of light for the use of infrared cameras, as well as the need to move our setup two times (from surface to surface) during an entire experiment. However, previous studies reported good agreement between 2D and 3D methods for lower body kinematics and kinetics during jumping ( Hickox et al, 2016 ). Since the CMJ task is mainly restrained to the sagittal plane, we assume that 2D high speed video is appropriate to appraise the influence of different surfaces on 2D joint kinematics ( Hickox et al, 2016 ).…”
Section: Discussionmentioning
confidence: 89%
“…However, previous studies reported good agreement between 2D and 3D methods for lower body kinematics and kinetics during jumping ( Hickox et al, 2016 ). Since the CMJ task is mainly restrained to the sagittal plane, we assume that 2D high speed video is appropriate to appraise the influence of different surfaces on 2D joint kinematics ( Hickox et al, 2016 ). Third, we used a simple foot model to capture ankle kinematics, which is then used to compute MTU length.…”
Section: Discussionmentioning
confidence: 89%
“…Since it was not possible to use a laboratory motion capture system outdoors, a high-speed video camera (300 frame.s –1 ; Casio Exilim EX-F1, Japan) was used to record the two-dimensional (2D) positions of six reflective markers placed on the right side of the participants at the following locations: the fifth metatarsal, lateral calcaneus, lateral malleolus, lateral femoral epicondyle, great trochanter, and the acromion. The camera axis was perpendicular to the sagittal plane of jumping to prevent from image distortion and inaccurate marker trajectories ( Kurokawa et al, 2003 ; Hickox et al, 2016 ). Marker trajectories were semi-automatically digitized (Dartfish ProSuite 9.0, Fribourg, Switzerland), low-pass filtered (8 Hz) ( Kurokawa et al, 2003 ) and used to retrieve marker coordinates.…”
Interactions between human movement and surfaces have previously been studied to understand the influence of surface properties on the mechanics and energetics of jumping. However, little is known about the muscle-tendon unit (MTU) mechanics associated with muscle activity and leg adjustments induced by different surfaces during this movement. This study aimed to examine the effects of three surfaces with different properties (artificial turf, hybrid turf, and athletic track) on the muscle mechanics and muscle excitation of the gastrocnemius medialis (GM) and vastus lateralis (VL) during maximal countermovement jumping (CMJ). Twelve participants performed maximal CMJs on the three sport surfaces. GM and VL muscle fascicles were simultaneously imaged using two ultrafast ultrasound systems (500 Hz). MTUs lengths were determined based on anthropometric models and two-dimensional joint kinematics. Surface electromyography (EMG) was used to record GM and VL muscle activity. Surface mechanical testing revealed systematic differences in surface mechanical properties (
P
= 0.006, η
2
: 0.26–0.32,
large
). Specifically, the highest force reduction and vertical deformation values have been observed on artificial turf (65 ± 2% and 9.0 ± 0.3 mm, respectively), while athletic track exhibited the lowest force reduction and vertical deformation values (28 ± 1% and 2.1 ± 0.1 mm, respectively) and the highest energy restitution (65 ± 1%). We observed no significant difference in CMJ performance between the three surfaces (∼35–36 cm,
P
= 0.66). GM and VL fascicle shortening (
P
= 0.90 and
P
= 0.94, respectively) and shortening velocity (
P
= 0.13 and
P
= 0.65, respectively) were also unaffected by the type of surface. However, when jumping from greater deformable surface, both GM muscle activity (
P
= 0.022, η
2
= 0.18,
large
) and peak shortening velocity of GM MTU (
P
= 0.042, η
2
= 0.10,
medium
) increased during the push-off phase. This resulted in a greater peak plantar flexion velocity late in the jump (
P
= 0.027, η
2
= 0.13,
medium
). Our findings suggest that maximal vertical jumping tasks in humans is not affected by common sport surfaces with different mechanical properties. However, internal regulatory mechanisms exist to compensate for differences in surface properties.
“…This model is limited to joints that are relevant for the task and includes some simplifications. A 3D model is required because, as shown in previous studies 42 , a simpler sagittal model is not sufficient to study the upper body motion during standing long jumps. Figure 3 Modeling of the human skeletal system.…”
The human body generally has more degrees of freedom than necessary for generating a given movement. According to the motor abundance principle, this redundancy is beneficial as it provides the central nervous system with flexibility and robustness for the generation of movements. Under the hypothesis of the Uncontrolled Manifold, the additional degrees of freedom are used to produce motor solutions by reducing the variability that affects the motion performance across repetitions. In this paper, we present a general mathematical framework derived from robotics to formulate kinematic and dynamic tasks in human movement. On this basis, an extension of the Uncontrolled Manifold approach is introduced to deal with dynamic movements. This extension allows us to present a complex experimental application of the proposed framework to highly dynamic task variables in parkour movements. This experiment involves dynamic tasks expressed in terms of linear and angular momenta. The results show that the central nervous system is able to coordinate such skilled tasks which appear to be preferentially controlled and hierarchically organized. The proposed extension is promising for the study of motion generation in anthropomorphic systems and provides a formal description to investigate kinematics and dynamics tasks in human motions.
“…Lateromedial GRFs were also controlled but negligible as the mean variation was lower than 0.5% of BW. In fact, the data showed that the SLJ can be considered and studied from the sagittal plane because the action of both limbs is symmetrical (Hickox, Ashby, & Alderink, 2016).…”
The present study aimed at investigating different variables that can be manipulated prior to and during takeoff , to execute a specific standing long jump (SLJ) distance, according to jump expertise in parkour practitioners (= traceurs). Fourteen healthy young traceurs were included and separated into two groups: beginners (BEG) and experts (EXP). Firstly, classical vertical jump battery was used to characterize participants arm use and leg efficiency. Secondly, standing long jump (SLJ) performances were analyzed at four distances: 70, 80, 90, and 100% of each participant's maximal SLJ distance. The force-time curves of the ground reaction forces (GRF) and the center of pressure (CoP) trajectory were measured with a force platform during the jump impulses. Takeoff speed, angle and jump trajectory were estimated. For all of the participants, takeoff speed and angle, power output, and vertical GRF during jump preparation (counter movement) varied with distance. The EXP group exhibited greater backward CoP excursion, greater arm participation, greater takeoff velocity and a greater modulation of takeoff angle than BEG group. When comparing jumps of similar distance, EXP exhibited a more curvilinear trajectory with a higher peak than BEG. To conclude, different motor strategies can be adopted based on the jump distance, and these strategies can evolve as parkour experience increases.
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