Sleep quality analysis method and device, computer equipment and storage medium

Abstract

The invention relates to a sleep quality analysis method and device, computer equipment, a readable storage medium and a computer program product. The method comprises the following steps: acquiring sleep-related signals of one-time complete sleep collected by the non-wearable device, wherein the sleep-related signals comprise a sleep audio signal and a human body sleep action signal; the sleep audio signals are input into a preset training model, a classification result of the sleep audio signals is obtained, and the classification result of the sleep audio signals comprises snore, dream or sleep environment noise; based on the human body sleep action signal, determining a division result of the sleep depth, the division result of the sleep depth including deep sleep or shallow sleep; and determining an analysis result of the sleep quality according to a classification result of the sleep audio signals and a division result of the sleep depth. Sleep environment noise is detected through an audio recognition algorithm, the sleep depth of a user is recognized through an acceleration sensor, and then sleep quality is judged through sleep environment sound sources and sleep depth recognition in a multi-dimensional mode.

Description

technical field [0001] The present application relates to the technical field of data analysis, in particular to a sleep quality analysis method, device, computer equipment and storage medium. Background technique [0002] With the improvement of living standards, after meeting the basic needs of food and clothing, people pay more and more attention to their own health. And sleep plays a vital role for the human body. About 1 / 3 of a person's life is spent in sleep. Problems with sleep health can lead to many adverse consequences, such as headaches, anxiety, and decreased immunity. Wait. [0003] At present, sleep analysis and identification mainly use the user's sleep duration, sleep time, and environmental noise monitoring during sleep as sleep quality analysis. Most of them use the user's manual input of sleep data to determine sleep quality, which is prone to misjudgment. And the sleep monitoring equipment in the prior art, from sleep mattress to smart wristband, althou...

AI Technical Summary

Problems solved by technology

[0003] At present, sleep analysis and identification mainly use the user's sleep duration, sleep time and environmental noise monitoring during sleep as sleep quality analysis. Most of them use the user's manual input of sleep data to determine sleep quality, which is prone to misjudgment.

And the sleep monitoring equipment in the prior art, from sleep mattress to smart bracelet, although various sensors can be used to monitor the sleep process, but all need supporting monitoring equipment, there are many inconveniences in use

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