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Three-factor method cuffless continuous blood pressure detection system based on artificial neural network

An artificial neural network and detection system technology, which is applied in the field of three-element cuffless continuous blood pressure detection system, can solve the problems of ignoring personal physical signs and only considering, and achieves portable cuffless continuous blood pressure detection, root mean square error Small, highly correlated effects

Pending Publication Date: 2020-07-17
TIANJIN UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of the current cuffless continuous blood pressure modeling input parameters only consider the parameters related to cardiovascular, focusing on the selection of models, but ignoring the relationship between personal signs and blood pressure

Method used

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  • Three-factor method cuffless continuous blood pressure detection system based on artificial neural network
  • Three-factor method cuffless continuous blood pressure detection system based on artificial neural network
  • Three-factor method cuffless continuous blood pressure detection system based on artificial neural network

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Embodiment 1

[0034] The embodiment of the present invention provides a three-element method based on artificial neural network cuffless continuous blood pressure detection system, see figure 1 , the system is divided into two parts: hardware circuit and data processing.

[0035] Wherein, the hardware circuit includes: an electrocardiographic signal acquisition circuit and a pulse wave signal acquisition circuit;

[0036] The core of the ECG signal acquisition circuit is an instrument amplifier, which differentially amplifies the ECG signal; when collecting the ECG signal, a high-frequency square wave signal is added, and over-sampling technology is used. The signal-to-noise ratio of the electrical signal improves the resolution of the ADC (analog-to-digital converter) for the ECG signal.

[0037] The core of the pulse wave signal acquisition circuit is a transimpedance amplifier circuit, which is used to realize the conversion of current and voltage when the pulse wave signal is measured ...

Embodiment 2

[0044] Combine below Figure 3-4 For a further introduction to the scheme in Example 1, see the following description for details:

[0045] The present invention recruited 184 volunteers, including 105 males and 79 females, with an age range of 18 to 72 years, a height range of 150 cm to 187 cm, and a weight range of 38.5 kg to 100 kg. Participants were not using any specific medications. Experiments were performed according to the Declaration of Helsinki. All subjects participated in this study voluntarily and signed a written consent form and experimental instructions before participation. The SBP and DBP values ​​of the right arm of the volunteers were measured three times with a conventional sphygmomanometer, and the average values ​​of the three SBP values ​​and DBP were taken as the reference values ​​for modeling. The sex, age, height and weight information of the volunteers were also asked and recorded during the measurement. In order to prevent the blood pressure ...

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Abstract

The invention discloses a three-factor method cuffless continuous blood pressure detection system based on an artificial neural network. The system predicts the blood pressure after three types of information of propagation time, a PPG waveform and personal characteristics are fused, and a hardware circuit includes an electrocardiogram (ECG) signal acquisition circuit based on shaped signals and oversampling, and a photoplethysmography (PPG) signal acquisition circuit based on a transimpedance amplifier circuit. The system uses oversampling and fast digital phase lock demodulation technology to simplify the circuit; filtering processing is performed on synchronously acquired PPG and ECG signals, the propagation time information (PTT) and the PPG waveform (PWPs) information are extracted, the personal characteristic parameters of the testees are recorded, and the neural network is used to establish a relationship model between PTT, PWPs and PCPs and the blood pressure; and the blood pressure value is predicted through the relationship model. Compared with a traditional cuffless blood pressure detection system, the blood pressure detection system proposed by the invention has highercorrelation and a lower root mean square error (RMSE) of blood pressure prediction results.

Description

technical field [0001] The invention relates to the field of blood pressure detection systems, in particular to a three-element cuffless continuous blood pressure detection system based on an artificial neural network. Background technique [0002] Blood pressure is one of the important physiological parameters reflecting the function of the human heart and blood vessels, and it is also an important basis for clinical disease diagnosis and data effect evaluation methods [1] . Since the 21st century, with the improvement of people's living standards, the accelerated pace of life, irregular living habits and other reasons, the incidence of stroke, myocardial infarction and other diseases caused by high blood pressure has become higher and higher. Therefore, the effective detection of human body Blood pressure plays a vital role in the prevention and control of hypertension and the chronic diseases caused by it. [0003] The current blood pressure measurement is mainly divide...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/021A61B5/0402A61B5/00
CPCA61B5/02108A61B5/02125A61B5/0059A61B5/6826A61B5/7207A61B5/7253A61B5/7275A61B5/318
Inventor 林凌尹帅举李刚
Owner TIANJIN UNIV
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