Kinematic algorithm to determine the energy cost of running with changes of direction

Zago, Matteo; Esposito, Fabio; Rausa, Giulia; Limonta, Eloisa; Corrado, Federica; Rampichini, Susanna; Sforza, Chiarella

doi:10.1016/j.jbiomech.2018.05.028

Cited by 7 publications

(16 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Mechanical energy during a CoD is an indirect measure of its associated metabolic cost. Computed positive/negative external CoM work was in line with previous investigations from different groups [8,16], which ensures the predictions were constructed on a solid basis. The prediction error (1.1–1.4 J) can be considered acceptable as it allows us to get a realistic measure of the amount of energy involved in the braking/propulsive actions, which is highly dependent on running speed.…”

Section: Discussionmentioning

confidence: 64%

“…The mechanics and neurophysiology of CoDs have been accurately described primarily in laboratory conditions, unveiling joint kinematics and loads as a function of the running angle and technique [1,9,10,11], foot-landing strategies [12], muscular activations [3,13], and response to fatigue [14,15]. In addition, we recently proposed an algorithm to estimate the energy cost of running with repeated 180 degree-CoDs [16]: the external mechanical energy associated to the trajectory of a body’s center of mass was combined with the knee flexion angle and ground contacts to provide an estimation of the positive (concentric) and negative (eccentric) muscular work.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Use of Machine Learning and Wearable Sensors to Predict Energetics and Kinematics of Cutting Maneuvers

Zago

Sforza

Dolci

et al. 2019

Sensors

View full text Add to dashboard Cite

Changes of directions and cutting maneuvers, including 180-degree turns, are common locomotor actions in team sports, implying high mechanical load. While the mechanics and neurophysiology of turns have been extensively studied in laboratory conditions, modern inertial measurement units allow us to monitor athletes directly on the field. In this study, we applied four supervised machine learning techniques (linear regression, support vector regression/machine, boosted decision trees and artificial neural networks) to predict turn direction, speed (before/after turn) and the related positive/negative mechanical work. Reference values were computed using an optical motion capture system. We collected data from 13 elite female soccer players performing a shuttle run test, wearing a six-axes inertial sensor at the pelvis level. A set of 18 features (predictors) were obtained from accelerometers, gyroscopes and barometer readings. Turn direction classification returned good results (accuracy >98.4%) with all methods. Support vector regression and neural networks obtained the best performance in the estimation of positive/negative mechanical work (coefficient of determination R2 = 0.42–0.43, mean absolute error = 1.14–1.41 J) and running speed before/after the turns (R2 = 0.66–0.69, mean absolute error = 0.15–018 m/s). Although models can be extended to different angles, we showed that meaningful information on turn kinematics and energetics can be obtained from inertial units with a data-driven approach.

show abstract

Section: Discussionmentioning

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Use of Machine Learning and Wearable Sensors to Predict Energetics and Kinematics of Cutting Maneuvers

Zago

Sforza

Dolci

et al. 2019

Sensors

View full text Add to dashboard Cite

show abstract

“…Immediately following the warm-up routine, athletes started the actual exercise protocol, that was extensively described elsewhere (Ciprandi et al, 2018;Zago et al, 2018Zago et al, , 2019 and involved a continuous 5-m shuttle run test designed to induce continuous 180 • turning actions (referred to as changes of direction, CoDs, in the following), repeated with alternated legs to avoid overloading. Running speed was set at an average value of 70% of each participant's maximum aerobic speed (MAS) and it was dictated by a beat counter.…”

Section: Methodsmentioning

confidence: 99%

“…The framework of analysis grounds on repeated turns as those performed in a continuous shuttle run test ( Ciprandi et al, 2018 ; Zago et al, 2018 , 2019 ); 180-degrees changes of direction are sport-specific tasks that can frequently occur during the game ( Jones et al, 2016b ) imply quick decelerations and high breaking forces to redirect the center of mass momentum ( Cortes et al, 2013 ); such forces can be counteracted by either eccentric muscle contractions and/or passive ligaments loading ( Besier et al, 2003 ; Jones et al, 2017 ). While jumps and heading actions were seldom the driver of ACL injuries in football ( Della Villa et al, 2020 ; Lucarno et al, 2021 ), the video analysis of ACL injuries in élite female players revealed that cutting actions like those involved in shuttle run are not only representative of soccer match-play ( Greig, 2009 ), but also a common non-contact injury pattern, especially in defensive “pressing and tackling” situations ( Lucarno et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Fatigue Induced by Repeated Changes of Direction in Élite Female Football (Soccer) Players: Impact on Lower Limb Biomechanics and Implications for ACL Injury Prevention

Zago

David

Bertozzi

et al. 2021

Front. Bioeng. Biotechnol.

Self Cite

View full text Add to dashboard Cite

BackgroundThe etiology of Anterior Cruciate Ligament (ACL) injury in women football results from the interaction of several extrinsic and intrinsic risk factors. Extrinsic factors change dynamically, also due to fatigue. However, existing biomechanical findings concerning the impact of fatigue on the risk of ACL injuries remains inconsistent. We hypothesized that fatigue induced by acute workload in short and intense game periods, might in either of two ways: by pushing lower limbs mechanics toward a pattern close to injury mechanism, or alternatively by inducing opposed protective compensatory adjustments.AimIn this study, we aimed at assessing the extent to which fatigue impact on joints kinematics and kinetics while performing repeated changes of direction (CoDs) in the light of the ACL risk factors.MethodsThis was an observational, cross-sectional associative study. Twenty female players (age: 20–31 years, 1st–2nd Italian division) performed a continuous shuttle run test (5-m) involving repeated 180°-CoDs until exhaustion. During the whole test, 3D kinematics and ground reaction forces were used to compute lower limb joints angles and internal moments. Measures of exercise internal load were: peak post-exercise blood lactate concentration, heart rate (HR) and perceived exertion. Continuous linear correlations between kinematics/kinetics waveforms (during the ground contact phase of the pivoting limb) and the number of consecutive CoD were computed during the exercise using a Statistical Parametric Mapping (SPM) approach.ResultsThe test lasted 153 ± 72 s, with a rate of 14 ± 2 CoDs/min. Participants reached 95% of maximum HR and a peak lactate concentration of 11.2 ± 2.8 mmol/L. Exercise duration was inversely related to lactate concentration (r = −0.517, p < 0.01), while neither%HRmax nor [La–]b nor RPE were correlated with test duration before exhaustion (p > 0.05). Alterations in lower limb kinematics were found in 100%, and in lower limb kinetics in 85% of the players. The most common kinematic pattern was a concurrent progressive reduction in hip and knee flexion angle at initial contact (10 players); 5 of them also showed a significantly more adducted hip. Knee extension moment decreased in 8, knee valgus moment increased in 5 players. A subset of participants showed a drift of pivoting limb kinematics that matches the known ACL injury mechanism; other players displayed less definite or even opposed behaviors.DiscussionPlayers exhibited different strategies to cope with repeated CoDs, ranging from protective to potentially dangerous behaviors. While the latter was not a univocal effect, it reinforces the importance of individual biomechanical assessment when coping with fatigue.

show abstract

“…Sin embargo, sorprendentemente, se han llevado a cabo pocas investigaciones para dilucidar los efectos del entrenamiento de fuerza excéntrico, o el entrenamiento de fuerza con acciones musculares excéntricas, acentuadas en el rendimiento de la velocidad de CoD. Zago, Esposito, Rausa, Rampichini & Sforza (2018), plantean un algoritmo cinemático para determinar el costo energético de correr con cambios de dirección. Los cambios de dirección (CoD) tienen un alto impacto metabólico y mecánico en los deportes de campo y de equipo de la cancha, pero la estimación de la carga de trabajo asociada sigue siendo inexacta.…”

Section: Enfoque Entrenamiento Deportivounclassified

Enfoques Teóricos Que Soportan El Programa De Ciencias Del Deporte Y La Actividad Física

Moreno¹,

Navarro²,

González³

2018

Enfoques, Teorías Y Perspectivas De Las Ciencias Del Deporte Y Sus Programas Académicos

View full text Add to dashboard Cite

Kinematic algorithm to determine the energy cost of running with changes of direction

Cited by 7 publications

References 35 publications

Use of Machine Learning and Wearable Sensors to Predict Energetics and Kinematics of Cutting Maneuvers

Use of Machine Learning and Wearable Sensors to Predict Energetics and Kinematics of Cutting Maneuvers

Fatigue Induced by Repeated Changes of Direction in Élite Female Football (Soccer) Players: Impact on Lower Limb Biomechanics and Implications for ACL Injury Prevention

Enfoques Teóricos Que Soportan El Programa De Ciencias Del Deporte Y La Actividad Física

Contact Info

Product

Resources

About