Fatigue sleep analysis method and device

An analysis method, sleep technology, applied in the fields of medical science, sensors, diagnostic recording/measurement, etc., to achieve the effect of a wide range of applications

Pending Publication Date: 2022-01-14
中国人民解放军海军特色医学中心
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Research on mental fatigue monitoring has a long history, but most of them need to be equipped with complex detection equipment. Therefore, it is very necessary to provide non-disturbing, portable, non-contact high-accuracy mental fatigue monitoring methods

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  • Fatigue sleep analysis method and device
  • Fatigue sleep analysis method and device
  • Fatigue sleep analysis method and device

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Embodiment Construction

[0055] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

[0056] In order to make the purpose, technical solutions and advantages of the embodiments of the application clearer, the technical solutions in the embodiments of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the application. Obviously, the described embodiments It is a part of embodiment of this application, and is not all embodiment. Based on the implementation manners in this application, all other implementation manners obtained by persons of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

[0057] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods may also be implemented in other wa...

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PUM

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Abstract

The invention discloses a fatigue sleep analysis method. The method comprises the following steps of step 1, collecting a BCG signal of a user; step 2, performing first filtering on the original BCG signal; step 3, carrying out second filtering on the original BCG signal; step 4, carrying out abnormal value elimination on the characteristic peaks; step 4, adopting a Lomb-Scargle algorithm for conducting power spectrum calculation on the respiration signals and the heart rate variability signals; step 5, conducting cardiopulmonary coupling analysis on the respiration signals and the heart rate variability signals; and step 6, classifying the cardiopulmonary coupling strength by adopting a classifier model in machine learning so as to obtain an analysis result of fatigue and sleep states. The method can process non-equidistant sampling signals, is not sensitive to the interference of abnormal points, and can obtain higher frequency precision. According to the algorithm, the detection precision of the algorithm is improved, the complexity of the algorithm is reduced, and the application range is wide.

Description

technical field [0001] The present application relates to the field of fatigue or sleep monitoring, in particular, to a fatigue sleep analysis method and device. Background technique [0002] Cardiac shock signal (Ballistocardiography, BCG) is a non-contact vital signs monitoring method, BCG signal and ECG Figure 1 It is also cyclical, reflecting the weak force changes on the support produced by the human heart when it periodically ejects blood, including chest heaving, heartbeat, body movement and other human activities during breathing. The acquisition methods of BCG signals include standing, sitting, lying and wearable. For a flat-lying BCG acquisition device, when a person lies flat on the mattress, respiration and heart ejection will produce a reaction force on the mattress below the person's body. Therefore, non-contact sleep monitoring based on BCG signals is possible. When a person sits on the cushion, breathing and heartbeat activities will also produce a reactio...

Claims

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Application Information

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IPC IPC(8): A61B5/11A61B5/0205
CPCA61B5/1102A61B5/0205A61B5/4806A61B5/02405
Inventor 何颖冯逸飞刘李娜王杨凯刘光盛
Owner 中国人民解放军海军特色医学中心
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