Sleep staging method based on decision-level fusion of multi-sensor data

A decision-level fusion and sleep staging technology, applied in the field of non-contact sleep staging, to achieve the effect of small data volume, scientific staging results, and strong fault tolerance

Active Publication Date: 2021-12-10
NANJING UNIV OF SCI & TECH
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  • Sleep staging method based on decision-level fusion of multi-sensor data
  • Sleep staging method based on decision-level fusion of multi-sensor data
  • Sleep staging method based on decision-level fusion of multi-sensor data

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[0287] The sleep staging method based on multi-sensor data decision-making level fusion of the present invention comprises the following steps:

[0288] Step 1. Tester: A male experimenter, 177cm in height, 23 years old, 70kg in weight, and 22.34 in BMI. Before the experiment, the experimenter was required to relax as much as possible, not to do strenuous exercise, and to eat regularly. During the experiment, the tester lay flat on the test bed, and the radar sensor was set directly above the human body to collect radar echo signals; the audio sensor was set toward the face to collect breathing and snoring signals;

[0289] Step 2. Turn on the radar sensor and audio sensor to collect overnight data. In the overnight data, the radar sensor data lasts 435 minutes, and the effective audio sensor data lasts 341 minutes;

[0290] Step 3. Connect the polysomnography recorder to the computer, export the results of sleep staging, save the signal data collected by the computer-side radar...

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Abstract

The invention discloses a sleep staging method based on multi-sensor data decision-making level fusion. The method first uses radar sensors and audio sensors to collect radar and audio data throughout the night, extracts radar and audio signal features; Classification, establish the radar residual segment model and the radar + audio segment model according to the data classification; then use the classifier to identify and classify the radar features in the radar residual segment model, and obtain the model prediction result 1, use the classifier to classify the radar + audio segment model The radar and audio features are identified and classified to obtain the model prediction results A and B; then the naive Bayesian model is used to make decisions on the model prediction results A and B, and the model prediction result 2 is obtained; finally, the model prediction result 1 and the model prediction result 2 Perform timing stitching to obtain the results of sleep staging throughout the night. The method is simple and easy to implement, with high accuracy, which is consistent with the actual situation.

Description

technical field [0001] The invention belongs to the technical field of vital sign monitoring and relates to a non-contact sleep staging method. Background technique [0002] During sleep, various physiological signals such as electroencephalogram and electrocardiogram change, and these signal changes have a certain correlation with the depth of sleep. In medicine, sleep is artificially divided into several stages based on physiological manifestations such as brain waves, electrocardiograms, and eye electricity. , The sleep stages throughout the night are also periodic and have certain rules. [0003] At present, sleep monitoring products mostly use contact monitoring, which requires a few electrodes to be attached to multiple parts of the subject's body, and wearing an oro-nasal airflow tube and an abdominal bandage. Contact monitoring greatly affects the physical and psychological conditions of the subjects, and the test environment is complex, requiring professional medi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/24147G06F18/24155G06F18/253
Inventor 顾陈周燕萍洪弘蒋洁李彧晟孙理朱晓华
Owner NANJING UNIV OF SCI & TECH
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