An electrocardiosignal prediction method and device based on Artificial Intelligence (AI), terminals (210, 320, 20), and a storage medium, applicable to the technical field of vital sign recognition. The method comprises: obtaining an electrocardiosignal of a target user (S401); importing the electrocardiosignal into a preset atrial fibrillation signal classification model, and obtaining a signal type of the electrocardiosignal output by the atrial fibrillation signal classification model (S402), wherein the atrial fibrillation signal classification model is obtained by training by using atrial fibrillation patients as model training samples; calculating a risk degree of onset of atrial fibrillation according to the signal type of the electrocardiosignal, and predicting whether the target user is about to develop atrial fibrillation (S403). The present invention can achieve the prediction of atrial fibrillation events, facilitate users to determine their own physical conditions, and improve a detection effect and the user experience.
ELECTROCARDIOSIGNAL PREDICTION METHOD AND DEVICE, TERMINALS, AND STORAGE MEDIUM