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Activity classification and analysis during sports training session using fuzzy model
- 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.
- Subjects :
- Statistics and Probability
business.industry
Computer science
Fuzzy model
General Engineering
Training (meteorology)
020206 networking & telecommunications
02 engineering and technology
Machine learning
computer.software_genre
Artificial Intelligence
Activity classification
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
Session (computer science)
business
computer
Subjects
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