Power Enhancement of Weightlifters during Snatch through Reducing Torque on Joints by Particle Swarm Optimization

In this research, an athlete's body on sagittal plane in tension phase of snatch weightlifting has been modeled in two dimensions for calculating the generated torques in joints. The error back propagation multi-layer perceptrons has been used for modeling the torque through changing the angular velocity, angular acceleration and absolute angle of each segment. Finally, the torque in joints has been minimized by particle swarm optimization technique and the power of athlete has been maximized. The method of weightlifting has been captured by high speed camera and the films have been analyzed through motion analysis software. Consequently, the required kinematic data for mathematical model of weightlifter has been produced. Unlike previous research reports, the technique of weightlifting has been modified with the aid of artificial neural network modeling to enhance athlete's power, instead of optimizing the effect of body parameters and sport facilities. In addition, this study focuses on computational intelligent techniques for optimization instead of classical methods.