Design and Validation of Rule-Based Expert System by Using Kinect V2 for Real-Time Athlete Support

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 28-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.

Kinect Azure–Based Accurate Measurement of Dynamic Valgus Position of the Knee—A Corrigible Predisposing Factor of Osteoarthritis

“…Kinect validation, a subtask of this study, was performed in order to be sure that the Kinect system is appropriate and reliable device for medical examination rooms, orthopedic physiotherapy practices or even gyms. Most studies in the literature with Kinect-based movement tracking systems use the earlier V2 camera [34][35][36], whereas in the present study we used the completely redesigned Kinect Azure, which has an advanced Time-of-Flight depth sensor and AI algorithm to identify joint midpoints. The validation of this camera system-even if it is limited to the single-leg squat-is a valuable resource for other investigators who are experimenting with the novel capabilities of Kinect Azure in various research settings.…”

The calculation of point quantity for lighting based on android OS using ionic framework and rule based expert system

“…The implementation of activities in this research uses the research and development model [13], while to develop an application program in overcoming lighting problems in lighting, researchers apply the existing formulas in building physics and are packaged in rule based expert systems [12], [14] and ionic framework [11], [15].…”

“…The sophistication of smartphone technology can be used to develop an application based on android programming that can be applied to calculate the need for light in room lighting by implementing lighting models in building physics so that it can help overcome these problems [9], [10]. This research was conducted with the aim of making an application produced in the form of an android program that will process the data that has been entered so that in a relatively short time it can be seen the results of the calculation of lamp light requirements for room lighting, including calculating the quantity of light points needed by utilizing the ionic framework design [11], which is combined with the method of rule based expert systems [12], so that an optimal solution for lighting can be obtained and at the same time can be achieved saving electricity consumption which in turn can save costs in lighting problems.…”

Towards an Innovative Model in Wearable Expert System for Skiing

“…Hermes et al [ 3 ] propose the detection of daily and sports activities with wearable sensors in a controlled and uncontrolled way. S Örücü et al [ 11 ] designed a real-time expert system for athletes comprising of an Expert System. Though skiing guidelines have been provided in the past to avoid possible accidents and relapses, the only existing expert system developed is by Sule Yildirim Yayilgan et al [ 19 ] This project focuses on parallel on the design of interfaces for mobile devices and in presenting an architecture for the digital recording of ski system injuries.…”