Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/1081
Title: Design and Validation of Rule-Based Expert System by Using Kinect V2 for Real-Time Athlete Support
Authors: Örücü, Serkan
Selek, Murat
Keywords: Expert System
Movement Modelization
Training Accuracy
Performance Enhancement
Injury Prevention
Sport
Human-Machine Interaction
Mild Cognitive Impairment
Reduced Rule
Shoulder
Performance
Validity
Reliability
Strength
Sport
Mechanisms
Stability
Issue Date: 2020
Publisher: MDPI
Abstract: In sports and rehabilitation processes where isotonic movements such as bodybuilding are performed, it is vital for individuals to be able to correct the wrong movements instantly by monitoring the trainings simultaneously, and to be able to train healthily and away from the risks of injury. For this purpose, we designed a new real-time athlete support system using Kinect V2 and Expert System. Lateral raise (LR) and dumbbell shoulder press (DSP) movements were selected as examples to be modeled in the system. Kinect V2 was used to obtain angle and distance changes in the shoulder, elbow, wrist, hip, knee, and ankle during movements in these movement models designed. For the rule base of Expert System developed according to these models, a 2(8)-state rule table was designed, and 12 main rules were determined that could be used for both actions. In the sample trainings, it was observed that the decisions made by the system had 89% accuracy in DSP training and 82% accuracy in LR training. In addition, the developed system has been tested by 10 participants (25.8 +/- 5.47 years; 74.69 +/- 14.81 kg; 173.5 +/- 9.52 cm) in DSP and LR training for four weeks. At the end of this period and according to the results of paired t-test analysis (p < 0.05) starting from the first week, it was observed that the participants trained more accurately and that they enhanced their motions by 58.08 +/- 11.32% in LR training and 54.84 +/- 12.72% in DSP training.
URI: https://doi.org/10.3390/app10020611
https://hdl.handle.net/20.500.13091/1081
ISSN: 2076-3417
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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