Sleep staging method based on BLSTM and sleep staging device based on BLSTM

A technology of sleep staging and sleep, applied in the field of sleep staging technology, which can solve the problems of low accuracy and prediction precision

Pending Publication Date: 2020-07-14
北京海思瑞格科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

At the same time, the traditional support vector machine algorithm was used to perform four-category sleep staging on the cardiop

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  • Sleep staging method based on BLSTM and sleep staging device based on BLSTM
  • Sleep staging method based on BLSTM and sleep staging device based on BLSTM
  • Sleep staging method based on BLSTM and sleep staging device based on BLSTM

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Embodiment Construction

[0143] Hereinafter, the present application will be described in detail in conjunction with the accompanying drawings.

[0144] A. Hardware

[0145] The wearable multi-sensor system SensEcho utilizes three comfortable electrode patches to acquire single-lead ECG signals at a sampling rate of 200Hz. Place the two lead wires under the chest and abdomen respectively, and collect two corresponding respiratory signals at a sampling rate of 25HZ. In addition, the three-axis digital acceleration component ADXL345 is embedded in the vest with a sampling rate of 25Hz and has ultra-low power consumption. The blood oxygen watch communicates wirelessly with SensEcho via Bluetooth, and the sampling rate is 1Hz. SensEcho can securely store data locally and in the cloud. 2GB of local data storage capacity can be back to the original data when the cloud storage is neither stable nor available. Embedded battery power supports 5 days of continuous monitoring. SensEcho's mainboard such as ...

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Abstract

The invention provides a sleep staging method based on BLSTM and a sleep staging device on the BLSTM. The BLSTM comprises two training layers and one output layer, wherein each training layer comprises 16 units, the output layer comprises 4 units, and the four units correspond to an awakening stage, a light sleep stage, a deep sleep stage and a rapid eye movement stage of sleep respectively; and input characteristics of the BLSTM comprise a characteristic extracted from an RR interphase signal, a characteristic extracted from a breathing signal and a characteristic extracted from cardiopulmonary coupling. The method and device acquire cardiopulmonary signals of a testee using a low-cost wearable multi-sensor system, conduct four-classification sleep staging by a bidirectional recursive neural network model which has an LSTM function and realize accurate staging of sleep.

Description

technical field [0001] This application relates to a sleep staging technique. Background technique [0002] Sleep quality is crucial to human health. Sleep quality is usually analyzed using physiological signals, which are not only related to physiological functions, but also have different patterns. Although there are multiple standards for sleep stages, the most common four-category sleep stage includes wakefulness, light sleep, deep sleep, and rapid eye movement. For example, deep sleep helps the body's metabolism and wound healing, while dreaming mostly occurs during rapid eye movement. Accurate sleep staging is important for sleep architecture to diagnose and restore sleep disorders. [0003] PSG is a standard method of sleep quality analysis, which can provide myoelectric activity in various parts of the body and has been used for sleep staging for the past few decades. This sleep staging method mainly relies on EEG signals, eye movement signals and myoelectric sig...

Claims

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Application Information

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IPC IPC(8): A61B5/0402A61B5/0452A61B5/08A61B5/00A61B5/1455
CPCA61B5/08A61B5/4812A61B5/7203A61B5/6802A61B5/725A61B5/02405A61B5/7267A61B5/7235A61B5/14551A61B5/14542A61B5/681A61B5/316A61B5/318A61B5/349
Inventor 兰珂郑捷文杨志诚郝艳丽
Owner 北京海思瑞格科技有限公司
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