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Activity classification and analysis during sports training session using fuzzy model

Authors :
Jingyi Xie
M. Anbarasan
A. Antonidoss
Li Zhang
Source :
Journal of Intelligent & Fuzzy Systems. :1-15
Publication Year :
2021
Publisher :
IOS Press, 2021.

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.

Details

ISSN :
18758967 and 10641246
Database :
OpenAIRE
Journal :
Journal of Intelligent & Fuzzy Systems
Accession number :
edsair.doi...........e24e9bf6c2689cfb512274499b5e50a2
Full Text :
https://doi.org/10.3233/jifs-219042