Title: Use of compensatory exercises for footballers in the youth sports center Objectives: The aim of the work is to identify the most common muscle imbalances and to create a compensation program for football players in the category of younger students U12 and U13 in the youth sports center. Methods: The research was based on the diagnosis of players using test exercises, which focused on the occurrence of muscle imbalances and erroneous movement stereotypes according to Bursová (2005), Hošková & Matoušová (2007) and Bursová et al. (2003). Detection was provided by selected functional muscle tests, which were applied in the input and output measurements. Correct performance of the exercise was evaluated as number 1. Incorrect performance was evaluated as number 2. After the initial measurement and evaluation of the degree of muscle imbalances, a compensation program was designed, whose primary task was to eliminate or alleviate muscle imbalances of individual players. The final measurement was used to verify the effectiveness of the compiled compensation program. A one - sample nonparametric Wilcoxon test was used in the work, the task of which was to confirm the validity of the used tests. Results: Due to the fact that the results of selected probands improved in most of the test exercises...

В области компьютерного зрения оценка позы человека приобретает все большее значение. Это одна из самых привлекательных областей исследований, и она вызывает большой интерес благодаря своей полезности и гибкости в самых разных областях, включая здравоохранение, игры, дополненную реальность, виртуальные тренировки и спорт. На ряду с этим люди все чаще начинают заниматься спортом. А в спорте травмы неизбежны. В данной статье предлагается приложение для оценки выполнения фитнес-упражнений, которое контролирует правильность техники и дает обратную связь по ее исправлению, что помогает уменьшить травматизм при занятиях. Предварительно обученная модель MediaPipe использовалась для оценки поз, по результатам которой вычисляются углы между конкретными суставами. / In the field of computer vision, human pose estimation is becoming increasingly important. This is one of the most attractive areas of research, and it is of great interest due to its usefulness and flexibility in a wide variety of fields, including healthcare, games, augmented reality, virtual training, and sports. Along with this, people are increasingly starting to do sports. And in sports, injuries are inevitable. This article offers an application for evaluating the performance of fitness exercises, which monitors the correctness of the technique and gives feedback on its correction, which helps to reduce injuries during classes. A pre-trained MediaPipe model was used to evaluate poses, based on the results of which the angles between specific joints are calculated.