Abstract: A method and apparatus for the detection, analysis, and identification of realistic human body and limb movements during sports actions for multiple uses comprises collecting the health information of the move, using the moves as a training and monitoring techniques in live usage settings, and as inputs to simulators and video game environments. At least one body-worn sensor transmits values wirelessly to a computing device that records the moves and calculates the health statistics then uses a machine-learning algorithm to analyze and identify the moves. These algorithms then output information and can simulate realistic moves, identify how far from these realistic moves the actual move is, and apply these moves to an electronic game. These algorithms, through various techniques, can distinguish movements, identify many different fine-grain movements, and enforce the full completion of these moves before registering them, thus preventing cheating in a realistic gaming scenario.