Single-Leg Landings Following a Volleyball Spike May Increase the Risk of Anterior Cruciate Ligament Injury More Than Landing on Both-Legs

Xu, Datao; Jiang, Xinyan; Cen, Xuanzhen; Baker, Julien S.; Gu, Yaodong

doi:10.3390/app11010130

Cited by 65 publications

(60 citation statements)

References 50 publications

(75 reference statements)

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“…By summarizing, we can affirm that the method proposed here could be positively exploited during training sessions since it only requires: (i) the execution of easy motor tasks typical of training programs, since their correct execution is shown to be correlate to the prevention of ACL injury [ 65 , 66 ] and (ii) the use of only one low-cost wearable inertial sensor, which has already been demonstrated to be useful for the assessment of ACL injury [ 67 ]. Using this protocol as a screening method, customized interventions could be implemented for the athletes identified as potentially at higher risk of injury.…”

Section: Discussionmentioning

confidence: 83%

A Machine-Learning Approach to Measure the Anterior Cruciate Ligament Injury Risk in Female Basketball Players

Taborri

Molinaro

Santospagnuolo

et al. 2021

Sensors

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Anterior cruciate ligament (ACL) injury represents one of the main disorders affecting players, especially in contact sports. Even though several approaches based on artificial intelligence have been developed to allow the quantification of ACL injury risk, their applicability in training sessions compared with the clinical scale is still an open question. We proposed a machine-learning approach to accomplish this purpose. Thirty-nine female basketball players were enrolled in the study. Leg stability, leg mobility and capability to absorb the load after jump were evaluated through inertial sensors and optoelectronic bars. The risk level of athletes was computed by the Landing Error Score System (LESS). A comparative analysis among nine classifiers was performed by assessing the accuracy, F1-score and goodness. Five out nine examined classifiers reached optimum performance, with the linear support vector machine achieving an accuracy and F1-score of 96 and 95%, respectively. The feature importance was computed, allowing us to promote the ellipse area, parameters related to the load absorption and the leg mobility as the most useful features for the prediction of anterior cruciate ligament injury risk. In addition, the ellipse area showed a strong correlation with the LESS score. The results open the possibility to use such a methodology for predicting ACL injury.

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Section: Discussionmentioning

confidence: 83%

A Machine-Learning Approach to Measure the Anterior Cruciate Ligament Injury Risk in Female Basketball Players

Taborri

Molinaro

Santospagnuolo

et al. 2021

Sensors

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“…Compared to other planes, the sagittal plane of motion amplitude was the largest, and the impact on lower limb injury was also the largest. Previous studies have shown that larger flexion angles of the knee and hip during landing may increase shock absorption and reduce joint reaction force, thereby reducing the risk of lower limb injury ( Markolf et al, 1995 ; Lee et al, 2018 ; Xu et al, 2021a ). In our study, BS depicted greater ankle, knee, and hip vertical reaction forces than NS, and reduced the risk of lower limb joint injuries.…”

Section: Discussionmentioning

confidence: 99%

“…The height and body mass of subjects were measured with a stadiometer and calibrated scale. Based on a previous study ( Xu et al, 2021a ), a total of thirty-six standard reflective markers (diameter: 12.5 mm) were labeled to the bilateral lower limbs and pelvis to track the lower limb’s motion trajectory. Figure 2A shows the reflective marker placement.…”

Section: Methodsmentioning

confidence: 99%

An Investigation of Differences in Lower Extremity Biomechanics During Single-Leg Landing From Height Using Bionic Shoes and Normal Shoes

Zhou

Baker

et al. 2021

Front. Bioeng. Biotechnol.

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Bionic shoes utilizing an actual foot shape sole structure can alter lower limb’s biomechanics, which may help in the development of specific training or rehabilitation programs. The purpose of this study was to investigate the biomechanical differences in the lower limb during a single-leg landing task using bionic shoes (BS) and normal shoes (NS). Fifteen healthy male subjects participated in this study, sagittal, and frontal plane data were collected during the landing phase (drop landing from 35 cm platform). Our study showed that BS depicted a significantly greater minimum knee flexion angle at initial contact (p = 0.000), a significantly greater minimum (initial contact) hip flexion angle at initial contact (p = 0.009), a significantly smaller sagittal plane total energy dissipation (p = 0.028), a significantly smaller frontal plane total energy dissipation (p = 0.008), a significantly smaller lower limb total energy dissipation (p = 0.017) than NS during the landing phase. SPM analysis revealed that BS depicted a significantly smaller knee joint vertical reaction force during the 13.8–19.8% landing phase (p = 0.01), a significantly smaller anterior tibia shear force during the 14.2–17.5% landing phase (p = 0.024) than NS. BS appears to change lower limb kinematics at initial contact and then readjust the landing strategies for joint work and joint reaction force, thereby reducing the risk of lower limb skeletal muscle injury. BS have great potential for future development and application uses, which may help athletes to reduce lower limb injury risk.

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“…An eight-camera motion capture system (Vicon Metrics Ltd., Oxford, UK) was used to record running kinematic data at a frequency of 200 Hz, and an in-ground force plate (AMTI, Watertown, MA, USA) which was located in the middle of an overground runway recorded the ground reaction forces at 1000 Hz; 36 retroreflective markers were fixed to the lower limb of each runner to track movement [27], as outlined in Figure 2. Baseline An eight-camera motion capture system (Vicon Metrics Ltd., Oxford, UK) was used to record running kinematic data at a frequency of 200 Hz, and an in-ground force plate (AMTI, Watertown, MA, USA) which was located in the middle of an overground runway recorded the ground reaction forces at 1000 Hz; 36 retroreflective markers were fixed to the lower limb of each runner to track movement [27], as outlined in Figure 2. Baseline data (pre-5 km running) were collected with the participant standing (static), and was then followed by running trials on the overground runway at their self-selected speed, which was considered as a "natural running pace".…”

Section: Methodsmentioning

confidence: 99%

Prolonged Running Using Bionic Footwear Influences Lower Limb Biomechanics

et al. 2021

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The running biomechanics of unstable shoes have been well investigated, however, little is known about how traditional neutral shoes in combination with unstable design elements and scientifically (bionic) designed shoes influence prolonged running biomechanics. The purpose of this study was to investigate biomechanical changes for a typical 5 km run and how footwear technology may affect outcomes. Sixteen healthy male recreational heel strike runners participated in this study, and completed two prolonged running sessions (neutral shoe session and bionic shoe session), with 7 to 10 days interval between sessions. A two-way repeated-measures analysis of variance (ANOVA, shoe × time) was conducted to determine any differences in joint biomechanics. Main effects for shoe type were observed at the ankle, knee and hip joints during the stance phase. In particular, decreased range of motion (ROM) was observed using the bionic shoes for all three joints, and the joint moments also had significant changes except for the frontal plane of the hip. Main effects for time were also observed at the ankle, knee and hip joints. The ROM of the sagittal plane in the knee and hip decreased post-5 km running. The reduction of ankle dorsiflexion, hip flexion, hip adduction and hip internal rotation angles were observed post-5 km running, as well as the increase of ankle eversion and external rotation, knee adduction and internal rotation angles. The kinetics also exhibited significant differences between pre-5 km running and post-5 km running. The interaction effects only existed in the ROM of the hip sagittal plane, hip adduction angle and hip internal rotation angle. The results suggested that bionic shoes could be beneficial for strengthening muscle control, enhancing postural stability and proprioceptive ability. Footwear personalization could be a solution that benefits runners, reduces injury risk and improves running performance.

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Single-Leg Landings Following a Volleyball Spike May Increase the Risk of Anterior Cruciate Ligament Injury More Than Landing on Both-Legs

Cited by 65 publications

References 50 publications

A Machine-Learning Approach to Measure the Anterior Cruciate Ligament Injury Risk in Female Basketball Players

A Machine-Learning Approach to Measure the Anterior Cruciate Ligament Injury Risk in Female Basketball Players

An Investigation of Differences in Lower Extremity Biomechanics During Single-Leg Landing From Height Using Bionic Shoes and Normal Shoes

Prolonged Running Using Bionic Footwear Influences Lower Limb Biomechanics

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