Sign information monitoring method and system based on multiple physiological parameters and CNN

Abstract

The invention discloses a sign information monitoring method and system based on multiple physiological parameters and a CNN. The sign information monitoring system comprises an integrated bracelet terminal, a route coordinator, a server, a monitoring center and a sign information monitoring module, wherein the integrated bracelet terminal is connected with the route coordinator and transmits collected blood pressure, oxyhemoglobin saturation, body surface temperature, heart rate and the like; the route coordinator is connected with the server and transmits data frames of a plurality of encoded physiological parameters; the server receives the data frame transmitted by the coordinator through the Ethernet port; various physiological parameters of the tested object can be obtained after decoding; the physiological parameters are processed and then displayed in real time through the monitoring center; the monitoring center is connected with the server and displays dynamic change curves of the multiple physiological parameters in real time; the sign information monitoring module is connected with the server; and the multiple physiological parameters stored in the server serve as inputof the sign information monitoring module. According to the sign information monitoring method, the features can be automatically extracted from the collected physiological parameters, and high-precision recognition is realized.

Description

technical field [0001] The invention relates to a technology in the field of pattern recognition, in particular to a method for monitoring sign information used in a wearable multi-physiological parameter monitoring system. Background technique [0002] Traditional medical equipment has the disadvantages of large volume, many lines, cumbersome operation, inconvenient movement and single function. With the development of sensor technology, wireless transmission technology, and miniaturization integration technology, wireless monitoring has been applied to the elderly, chronic disease patients, and postoperative rehabilitation patients due to its advantages of integrated measurement of multiple physiological parameters, flexibility, portability, non-invasiveness, intelligence and high efficiency. and many other groups. [0003] Traditional pattern recognition methods require domain-specific expertise to design and extract features, and the designed features are not universal,...

AI Technical Summary

Problems solved by technology

[0004] In view of the above-mentioned deficiencies in the prior art, as well as the problems in real-time monitoring of traditional medical equipment and the deficiencies in traditional pattern recognition methods, the present invention proposes a method and system for monitoring sign information based on multiple physiological parameters and CNN. Based on the problems of single function and complicated operation of traditional medical equipment, CNN model is used for sign information monitoring. Compared with traditional pattern recognition methods, CNN can automatically extract features from collected physiological parameters and achieve high-precision identify

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