IMU action recognition based on machine learning

The invention belongs to the field of artificial intelligence. It is a gesture recognition system based on mechanical learning. The invention comprises the following steps: Firstly, we adopt Arduino development environment. Secondly, we choose RBF algorithm. Third, mechanical learning of motion recognition. By constantly adjusting the parameters of the algorithm, such as the basic learning rate and the value of r, the model will achieve optimal performance. Finally, the action test set is input into the training system to identify different types of actions accurately, and the accuracy of the algorithm is estimated through a large number of experiments. In short, the invention can recognize different kinds of gestures by mechanical learning, and has high accuracy.