Random forest-based sleep staging method and system

A sleep staging and random forest technology, applied in the computer field, can solve problems such as low classification accuracy, and achieve the effects of improving accuracy, removing electrooculography artifacts, and improving accuracy

Pending Publication Date: 2019-04-12
HANGZHOU NEURO TECH CO LTD
View PDF7 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the problem of low classification accuracy in the existing sleep staging metho

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Random forest-based sleep staging method and system
  • Random forest-based sleep staging method and system
  • Random forest-based sleep staging method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The EEG signals in the sleep state usually contain a lot of physiological information about human diseases, so in order to conduct better research, it is necessary to stage sleep. The existing staging methods are difficult to completely and accurately extract the sleep information contained in the EEG data and are prone to overfitting problems in classification, which greatly affects the accuracy of sleep staging. In view of this, the present embodiment provides a sleep staging method and system based on random forest.

[0040] Such as figure 1As shown, the present embodiment provides a sleep staging method comprising: acquiring a plurality of brain signal samples and performing sleep staging on each brain signal sample (step S10 ). Perform preprocessing on each EEG signal sample (step S20). Each preprocessed EEG signal sample is divided into multiple segments with a certain duration from the time domain (step S30). Extracting multiple feature parameters on each segm...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a random forest-based sleep staging method and system. The method is as follows: acquiring a plurality of EEG signal samples and performing sleep staging on each EEG signal sample; preprocessing each EEG signal sample; segmenting each pre-processed EEG signal sample into a plurality of segments having a certain duration; extracting a plurality of characteristic parameters oneach segment, wherein the plurality of characteristic parameters include time domain characteristic parameters, frequency domain characteristic parameters, and non-linear characteristic parameters; training a plurality of decision trees in a random forest classifier with the extracted characteristic parameters as the characteristic vectors to form a random forest model; acquiring an EEG signal tobe analyzed; after preprocessing, segment segmentation and characteristic extraction, inputting the EEG signal to be analyzed into the random forest model to obtain sleep staging of the EEG signal tobe analyzed.

Description

technical field [0001] The invention relates to the field of computers, and in particular to a random forest-based sleep staging method and system. Background technique [0002] Sleep is a very important physiological activity of the human body. It is a physiological phenomenon for human beings to adapt to the day and night changes in nature. It is easily affected by environmental, emotional and other factors. After continuous research, we found that sleep has certain physiological rules, and we can get a lot of physiological information from sleep electroencephalogram signals (EEG). Therefore, studying the information contained in sleep EEG signals and analyzing the changes in sleep cycles is of great significance for the study of sleep-related diseases. At present, the sleep staging rules of the American Academy of Sleep Medicine (AASM) are widely used in the world. According to the characteristics of EEG during sleep, sleep can be divided into: wakefulness (W), non-rapid...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): A61B5/0476G06K9/00G06K9/62
CPCA61B5/4806A61B5/7203A61B5/7253A61B5/7267A61B5/369G06F2218/02G06F2218/08G06F2218/12G06F18/24323
Inventor 戴珅懿刘俊飙吴端坡李凯蔡晨毅
Owner HANGZHOU NEURO TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap