Disclosed are a training method and a training apparatus for a continuous motion information prediction model, and a computer-readable storage medium. The training method comprises: acquiring a training sample and hidden state initial data of the current time period, wherein the training sample of the current time period comprises surface electromyography feature data on a plurality of spatial positions of the current time period; inputting the training sample and the hidden state initial data of the current time period into a continuous motion information prediction model to be trained, and performing calculation to obtain motion state prediction data and hidden state update data of the current time period; updating a loss function according to acquired motion state real data of the current time period and the calculated motion state prediction data of the current time period; and updating a network parameter of said continuous motion information prediction model according to the updated loss function. During a training process, information of a spatial dimension and a temporal dimension of surface electromyography feature data is fully utilized, which is conducive to improving the accuracy of a prediction model, and enhancing the real-time performance.
TRAINING METHOD AND TRAINING APPARATUS FOR CONTINUOUS MOTION INFORMATION PREDICTION MODEL, AND COMPUTER-READABLE STORAGE MEDIUM