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

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...

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

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