Innovative exploration of extracurricular physical exercise mode for college students integrating biomechanics and information technology
Abstract
Traditional college physical education courses require innovative methods of instruction in the wave of informatization education to stay with current trends. This study examines novel forms of physical exercise that college students can engage in outside the classroom by fusing cutting-edge information technology and advanced biomechanics. This study assesses the impact of these integrations on student engagement and physical health by utilizing methods including wearable sensors for real-time motion tracking, deep learning algorithms for pattern identification, and augmented reality (AR) for immersive training experiences. To improve the accuracy of reading movement intentions, data from 130 participants, including cardiorespiratory signals, heart rates, and motion imagery, were processed using a Binary Spotted Hyena Optimized Efficient Visual Geometry Group Network (BSHO-EVGGN). The findings show that these technology advancements greatly enhance students’ motivation and exercise performance in addition to providing real-time physiological metrics monitoring. The evaluation’s findings demonstrate how this strategy, which has received significant student support, considerably raises students’ learning performance and engagement. Enhancing the effectiveness and efficiency of teaching physical exercise is made possible by the creative use of physical teaching models in college physical education.
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