Abstract
Sport training is a sporting performance preparation phase that consists of four parts: Training in conditioning, technical Training, Training in attitude, Training in psychology. The challenging factor of the sports training session is the realization of approximate and uncertainty. The valued idea involves the definition of fuzzy sets and rules and membership functions to overcome the challenges. A fuzzy logical explanation enables successful ambiguous situations, which are complex, continuous, and more practical, closer to the real world and human thought. The concept, which is highly valued, includes defining fluids and rules and membership functions to test training exercises for strength. This paper proposed a Fuzzy, assisted artificial intelligence monitoring framework (FAAIMF) that evaluates all athletes’ behaviors in an outdoor training setting using wearable inertial sensors. Data obtained from sensor fitted machines, feedback, and proper implementation requirements are considered in the design. The Random Forest Classifier uses a Discreet Transform Wavelet (DWT) to effectively and accurately effectively and accurately id. Second, the relative orientation of the wearable inertial sensors on a shield and thigh of a material from which the knee angle of flexion-extension is determined. The proposed method in various non-constrained settings for the exact classification of sports activities and accurate movement techniques assessment.
Published Version
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