Deep learning-based user sleep behavior analysis method and system

A technology of deep learning and behavior analysis, applied in the field of sleep monitoring, can solve problems such as inability to record and analyze sleep status, incomplete quality service functions, etc., and achieve the effect of adding suggestions, improving sleep quality, and strong sharing

Pending Publication Date: 2021-11-16
DALIAN NEUSOFT UNIV OF INFORMATION
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0003] The present invention provides a user sleep behavior analysis method and system based on deep learning to overcome the problems of incomplete quality service function of existing sleep monitoring sensor equipment, inability to analyze sleep state according to real-time recording, etc.;

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  • Deep learning-based user sleep behavior analysis method and system
  • Deep learning-based user sleep behavior analysis method and system
  • Deep learning-based user sleep behavior analysis method and system

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Embodiment Construction

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0042] This embodiment provides a user sleep behavior analysis method based on deep learning, such as figure 2 , characterized by including:

[0043] Step 1. Collect the open source sleep audio signal, and obtain the zero crossing rate, spectrum center, spectrum roll-off point and MFCC data of the open source sleep audio signal sample data by Fo...

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Abstract

The invention discloses a deep learning-based user sleep behavior analysis method and a deep learning-based user sleep behavior analysis system. The system comprises a recording module, a sleep analysis module and a report generation module, the recording module is used for recording user sleep audio, and the sleep analysis module is used for obtaining a sleep audio average decibel value of a user by using the user sleep audio, wherein the sleep audio average decibel value is compared with the sleep characteristic value; the report generation module is used for generating a corresponding report according to the sleep state of the user, and by adopting the mode of recording sleep and analyzing the recorded audio to generate the sleep report, more people can conveniently know the sleep behaviors of themselves, clearly know the sleep conditions of themselves and improve the sleep quality of themselves; and thereby, a good sleep habit is developed.

Description

technical field [0001] The present invention relates to the technical field of sleep monitoring, in particular to a user sleep behavior analysis method and system based on deep learning. Background technique [0002] Most of the existing sleep monitoring sensing devices are located in hospitals and are expensive and difficult to carry. At the same time, the existing sleep monitoring sensing devices do not have the function of analyzing sleep status based on real-time sleep recordings, and cannot accurately capture, store, analyze and Manage sleep audio data, so the sleep quality service is not fully functional. Contents of the invention [0003] The present invention provides a user sleep behavior analysis method and system based on deep learning to overcome the problems of incomplete quality service function of existing sleep monitoring sensor equipment, inability to analyze sleep state according to real-time recording, etc.; [0004] In order to achieve the above object...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00G06F16/2458G06F16/248G06F16/28G06N3/04G06N3/08G06Q30/06G16H15/00G16H50/70G16H70/00
CPCA61B5/4806A61B5/4809A61B5/4815G06N3/08G06Q30/0601G06F16/2462G06F16/248G06F16/284G16H50/70G16H15/00G16H70/00G06N3/045
Inventor 王骏美朱文操
Owner DALIAN NEUSOFT UNIV OF INFORMATION
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