Sleep regulation method, device and equipment fusing millimeter wave radar and large model

Abstract

The present application relates to the technical field of nursing, solves the problem that the millimeter wave radar sleep monitoring parameter is fixed, lacks personalized learning and large model fusion in the prior art, which leads to difficulty in accurately detecting sleep posture and evaluating sleep quality, and provides a sleep regulation method, device and equipment fusing millimeter wave radar and a large model. The method comprises the following steps: inputting basic information and sleep data of a target object into a neural network model, obtaining millimeter wave radar signals output by the adjusted millimeter wave radar and nursing environment data according to obtained personalized modeling data; performing feature extraction on the preprocessed millimeter wave radar signals to obtain breathing profile amplitude features and radar point cloud micro-motion features, and inputting the features and the nursing environment data into a large model, and generating sleep regulation suggestions for the target object according to generated sleep posture detection results and sleep quality evaluation results. The present application improves the accuracy of sleep posture detection and sleep quality evaluation for different groups of people.

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