Non-invasive continuous blood pressure measurement method based on deep neural network

A technology of deep neural network and processing method, applied in the field of non-invasive continuous blood pressure calculation, which can solve problems such as insufficient robustness, dependence, and difference

Active Publication Date: 2018-09-07
BEIJING UNIV OF POSTS & TELECOMM
View PDF9 Cites 41 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method is very dependent on the selection of features manually, and the quality of feature selection is directly related to the prediction accuracy.
In addition, for different forms of pulse waves collected by different measuring devices, the selected features may vary greatly
This shows that this method is too subjective and not robust enough

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
  • Non-invasive continuous blood pressure measurement method based on deep neural network
  • Non-invasive continuous blood pressure measurement method based on deep neural network
  • Non-invasive continuous blood pressure measurement method based on deep neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0096] The present invention will be specifically introduced below in conjunction with the accompanying drawings and specific embodiments.

[0097] The technical scheme of the present invention is as figure 1 As shown, it mainly includes preprocessing the collected original pulse wave signal, and then inputting it into the deep neural network model to obtain the blood pressure value.

[0098] The pulse wave sampling rate is usually 125Hz. In the acquisition of the original pulse wave signal and the preprocessing part, it is necessary to divide the collected time-domain pulse wave signal into a series of periodic segments, then perform filtering processing, and finally process it into equal long period segments. First, you need to process the periodic segment data:

[0099] 1.1) Output a small section of waveform. Through observation, it is estimated that the cycle length of the wave is L predict points, the predicted value should be greater than the observed cycle length, t...

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 non-invasive continuous blood pressure measurement method based on deep learning. The measurement method mainly comprises a pulse wave signal preprocessing method, a deep neural network model establishing method and a blood pressure measuring method. Pulse wave signals input to a neural network are subjected to preprocessing, filtering and noise reduction and normalizationprocessing, so that an established model is more accurate and has better adaptability. The method uses a deep neural network, subjective feature extraction and complex mathematical modeling problemsare avoided, and the network can conduct blood pressure measurement on different forms of pulse waves of different individuals through a large number of data training networks and can be applied to awide range of blood pressure prediction scenarios after the network is trained for once. Compared with the prior art, the objectivity is high, the model robustness is strong, and the measurement method is suitable for integration in home medical monitoring equipment and is also suitable for blood pressure monitoring of a wearable device.

Description

technical field [0001] The invention relates to the field of digital signal processing, in particular to a method for non-invasive and continuous blood pressure calculation based on digital signal processing. Background technique [0002] Blood pressure (BP) is an important parameter that reflects the performance of the human circulatory system. Checking blood pressure is a major method for clinically judging diseases and observing the effect of treatment. Humans are afflicted by many diseases related to arterial blood pressure (ABP), including hypertension and heart disease. Therefore, the monitoring of blood pressure is of great significance. [0003] At present, blood pressure measurement methods can be roughly divided into two categories: direct measurement method and indirect measurement method: the direct measurement method needs to insert the catheter connected with the pressure sensor directly into the aorta or heart. This method has the highest measurement accuracy...

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
Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/021G06N3/04G06N3/08
CPCA61B5/02108G06N3/08A61B5/7203A61B5/7225A61B5/7267G06N3/045
Inventor 袁学光张阳安杨帆
Owner BEIJING UNIV OF POSTS & TELECOMM
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