Twelve-week sensorimotor training as a factor influencing movement patterns of canoe slalom athletes, assessed by the Functional Movement Screen

REDUCING THE SPORTS INJURY THROUGH FUNCTION MOVEMENT BIOLOGICAL IMAGE DATA SCREENING

ABSTRACT Introduction Among the many cases of sports injuries, the incidence of musculoskeletal injuries remains high. After a musculoskeletal injury occurs, athletes often need to suspend training and undergo rehabilitation. A suitable sport mode requires athletes to have sufficient joint range of motion, core stability, and balance ability in different positions to complete various complex movements in training and competition. Objective The paper analyzes the impact of warm-up exercises before the test on the test results of functional sports biological image data screening ( FMS TM ) and provides references for unifying test conditions, checking the reliability of FMS TM repeated tests, and discussing the comparability of the research results. Methods The paper used the same password and process to test 12 young male volleyball professional athletes without warm-up and warm-up. The two-dimensional motion analysis system Dartfish Pursuit 8.0 was used to analyze the video data recorded by the two cameras simultaneously. Results In the two tests before and after, the hurdle step score (1.75±0.62 vs. 2.42±0.52) and the total score (13.50±2.20 vs. 16.42±2.15) were significantly higher than those without the warm-up test (P<0.01). Besides, in squats (1.58±0.67 vs. 1.92±0.67), straight lunges (2.00±0.43 vs. 2.50±0.52), active straight leg lifts (1.50±0.67 vs. 2.00±0.60), rotation stability (1.42) ±0.52 vs. 1.92±0.29) showed a significant increase in the score (P<0.05). Conclusions Warm-up exercises before the test can improve the test results. This abnormal movement pattern observed only by visual inspection may not truly reflect the “dysfunction” of the movement. In the case of ignoring the pre-test warm-up factors, feedback on sports performance and formulating training strategies, this conclusion of predicting injury risk and evaluating training effects may have specific limitations in its reference value. Level of evidence II; Therapeutic studies - investigation of treatment results.

Artificial intelligence based tracking model for functional sports training goals in competitive sports

As an advanced training concept, functional physical training is gradually recognized by top athletes for its high training effect and low sports injury. Functional physical training should gradually develop from elite athletes to grassroots athletes, so as to lay a solid foundation for the development of competitive sports. Because particle filtering is susceptible to external factors in moving target tracking, this paper designs a method for sparse coding using local image blocks of the target, establishes a static “impression” and dynamic model for the appearance of the target. The tracking problem is regarded as a binary classification problem between the foreground target and the background image. During the tracking process, the dual particle filter is implemented to alleviate the tracking drift, so that the algorithm can adaptively capture the changes in the target appearance At the same time, it can reduce the update caused by wrong positioning. The subjects’ FMS test and Y balance test have improved in varying degrees; the pressure distribution of the forefoot, arch, and heel tends to be rationalized, and the ratio of internal and external splayed feet has decreased. Experiments show that this particle filter moving target tracking scheme can adapt to changes in the environment and overcome the inflexibility of the global template when dealing with local changes in the target.