| Creating a real-time automated coach assistance for shooting sports by using image processing techniques and making EMG signal detection device |
| Paper ID : 1570-SSRC-13TH |
| Authors |
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Amir Alizadeh *1, Alireza Shams Asr2 1Azad University, Tabriz Branch 2Tabriz Robotics and Mechatronics Institute |
| Abstract |
| Today, sports clubs use interdisciplinary technology to increase their professional competitiveness at basic educational levels. Utilizing new engineering methods and artificial intelligence in order to analyze and identify the correct positions of athletes, can improve the traditional standards of coaches. In gun shooting sport, the angles of the hands, shoulders, and head and feet have a great impact on correct shooting and there are some rules that the athlete must follow in order to gain more points and prevents anatomical injuries. In this regard, machine vision and electromyography signals can play an important role in detecting athletes' body movements. In this research, by using image processing programming in Borland Delphi 7 languages, a real-time method for detecting the effective angles of the shooter while shooting is presented. One camera is used for top view to calculate the angle of the shooter's hand, head and shoulders relative to the X-axis and the position of the floor, and the second camera is used for lateral view to calculate the angle of the trigger finger, wrist, and elbow with z-axis and Knees and legs distance. By designing and making a single-channel electromyography with surface electrodes made of silver, the tension of one of the biceps or deltoid or Supraspinatus muscles is effective while shooting is measured. In this circuit, an active band pass filter between 10 and 600 Hz along with a 50 Hz active notch filter and a signal shifter is used. By hybrid image processing programming with real-time processing rate of 5 frame per second and electromyography signal analysis is a convenient way to monitor shooter performance which can help instructors make training decisions as a real-time and automated assistant coach. |
| Keywords |
| Shooting sports, Electromyography signals, Assistant coach, Real Time, Image Processing; |
| Status: Abstract Accepted (Oral Presentation) |
