Background: Female soccer players are particularly susceptible to anterior cruciate ligament (ACL) injuries, accounting for 16% to 43% of the injury burden during the season. Despite the advancements in injury prevention programs, the rate of ACL injuries continues to rise. Purpose: To provide a comprehensive description of the mechanisms, situational pattern, and biomechanics of ACL injuries in women’s soccer. Study Design: Case series; Level of evidence, 4. Methods: We identified 57 consecutive ACL injuries that occurred in matches of 6 top female leagues across 3 seasons (2017-2020). A total of 35 (61%) injury videos were analyzed for the mechanism and situational pattern, while biomechanical analysis was possible in 29 cases. Three independent reviewers evaluated each video. The distribution of ACL injuries according to month, timing within the match, and field location at the time of injury was also reported. Results: In the 35 injury videos, there were 19 (54%) noncontact injuries, 12 (34%) indirect contact injuries, and 4 (11%) direct contact injuries. We identified 3 main situations in players who suffered a noncontact/indirect contact injury: (1) pressing and tackling (n = 18), (2) regaining balance after kicking (n = 7), and (3) being tackled (n = 4). Biomechanical analysis indicated multiplanar mechanisms with frequent knee valgus loading (88%). Additionally, 64% of injuries occurred in the first half of matches and most frequently within the first 30 minutes. Conclusion: Female athletes showed remarkable similarities with elite male players in terms of the ACL mechanism and situational pattern of injury, and 88% of injuries involved no direct contact to the knee, with noncontact injuries being highly prevalent. Injuries occurred during 3 main situations, with accompanying alterations in multiplanar biomechanics. Interventions aimed at reducing ACL injuries in women’s soccer should consider high-intensity defensive play at the beginning of a match. Instruction in the 3 main situations should be applied alongside appropriate neuromuscular training interventions.

The design of markerless systems to reconstruct human motion in a timely, unobtrusive and externally valid manner is still an open challenge. Artificial intelligence algorithms based on automatic landmarks identification on video images opened to a new approach, potentially e-viable with low-cost hardware. OpenPose is a library that t using a two-branch convolutional neural network allows for the recognition of skeletons in the scene. Although OpenPose-based solutions are spreading, their metrological performances relative to video setup are still largely unexplored. This paper aimed at validating a two-cameras OpenPose-based markerless system for gait analysis, considering its accuracy relative to three factors: cameras' relative distance, gait direction and video resolution. Two volunteers performed a walking test within a gait analysis laboratory. A marker-based optical motion capture system was taken as a reference. Procedures involved: calibration of the stereoscopic system; acquisition of video recordings, simultaneously with the reference marker-based system; video processing within OpenPose to extract the subject's skeleton; videos synchronization; triangulation of the skeletons in the two videos to obtain the 3D coordinates of the joints. Two set of parameters were considered for the accuracy assessment: errors in trajectory reconstruction and error in selected gait space-temporal parameters (step length, swing and stance time). The lowest error in trajectories (~20 mm) was obtained with cameras 1.8 m apart, highest resolution and straight gait, and the highest (~60 mm) with the 1.0 m, low resolution and diagonal gait configuration. The OpenPose-based system tended to underestimate step length of about 1.5 cm, while no systematic biases were found for swing/stance time. Step length significantly changed according to gait direction (p = 0.008), camera distance (p = 0.020), and resolution (p < 0.001). Among stance and swing times, the lowest errors (0.02 and 0.05 s for stance and swing, respectively) were obtained with the 1 m, highest resolution and straight gait configuration. These findings confirm the feasibility of tracking kinematics and gait parameters of a single subject in a 3D space using two low-cost webcams and the OpenPose engine. In particular, the maximization of cameras distance and video resolution enabled to achieve the highest metrological performances.

Gait variability can be considered an indirect measure of gait stability, in particular regarding temporal or spatial variability assessment. Physical activity, such as walking, is advised for the elderly and can be improved by gait stability. The aim of this study was to investigate the associations between gait stability and physical activity in women of different age ranges. Forty-two healthy women of different age ranges (18-40 yrs. and 65-75 yrs.) were recruited in the study. To assess physical activity, the subjects wore a multi-sensor activity monitor for a whole week, inferring the time spent in moderate to vigorous physical activity (MVPA). MVPA were analysed in bouts of at least 10 subsequent minutes (MVPAbouts) and in overall minutes (MVPAtot). A kinematic analysis was performed with an optoelectronic system to calculate gait variability - expressed as standard deviation (SD) and coefficient of variability (CV) of step width, stride length, stance and swing time (during treadmill walking at different speeds). Elderly women, with high walking speed (5 km/h), and moderate step width variability (CV = 8–27%), met the recommended levels of physical activity (MVPAtot and MVPAbouts). Furthermore, gait variability, adjusted for age and number of falls, was significantly and negatively associated with MVPAtot only at 3.5 km/h, and with MVPAbouts only at 4 km/h. In a population of healthy elderly women, gait variability was significantly and negatively associated with the level of physical activity. Healthy elderly women, with moderate gait variability (step width variability), and high preferred walking speed, seem to be able to meet the recommended levels of physical activity.

(i) to determine the outcomes of whole-body vibration training (WBVT) on obese individuals, and the intervention settings producing such effects; (ii) identify potential improper or harmful use of WBVT. Systematic review. Medline, Scopus, Web of Science, PEDro and Scielo until July 2018. Full papers evaluating the effect of WBVT on body composition, cardiovascular status and functional performance in obese adults. Papers with PEDro score<4 were excluded. Risk of bias and quality of WBVT reporting were assessed with PEDro scale (randomized controlled trials) or TREND checklist (non-randomized studies) and a 14-items checklist, respectively. Weighted acceleration, daily exposure and Hedges’ adjusted g were computed. We included 18 papers published 2010–2017. Typical interventions consisted in three sessions/week of exercises (squats, calf-raises) performed on platforms vibrating at 25–40 Hz (amplitude: 1–2 mm); according to ISO 2631–1:1997, daily exposure was “unsafe” in 7/18 studies. Interventions lasting ≥6 weeks improved cardiac autonomic function and reduced central/peripheral arterial stiffness in obese women; 10 weeks of WBVT produced significant weight/fat mass reduction, leg strength improvements as resistance training, and enhanced glucose regulation when added to hypocaloric diet. No paper evidenced losses of lean mass. Isolated cases of adverse effects were reported. To date, WBVT is a promising adjuvant intervention therapy for obese women; long-term studies involving larger cohorts and male participants are required to demonstrate the associated safety and health benefits. The therapeutic use of WBVT in the management of obese patients is still not standardised and should be supported by an extensive knowledge on the causality between vibration parameters and outcomes.