Remote breath diagnosis system based on Arduino cloud microprocessor

Abstract

The invention discloses a remote breath diagnosis system based on an Arduino cloud microprocessor. The diagnosis system comprises an acquisition device, user equipment, a cloud server and terminal equipment, wherein the acquisition device with the Arduino cloud microprocessor inside is used for acquiring concentration data of organic matters in gas exhaled by a user and wirelessly transmitting theacquired concentration data of the organic matters to the user equipment. The user equipment comprises an upper computer for uploading the received concentration data of the organic matters to the cloud server, the cloud server is used for calculating and processing the uploaded concentration data of the organic matters and then outputting detection results to the terminal equipment, so that medical staff can diagnose diseases according to the detection results, the terminal equipment is connected with the upper computer through a network, and online illness state diagnosis and communicationbetween the medical staff and the user can be realized. The shortcoming of large errors of traditional equipment is overcome by the aid of a sensor array and a neural network algorithm, and the remotebreath diagnosis system has the advantages of detection sensitivity, high reliability and convenience in operation.

Description

technical field [0001] The invention belongs to the field of medical technology, in particular to a remote respiratory diagnosis system for medical diagnosis using gas components exhaled by people, specifically a remote respiratory diagnosis system based on an Arduino cloud microprocessor. Background technique [0002] Lung cancer is one of the malignant tumors with the fastest growing morbidity and mortality in the world. A large number of data show that long-term heavy smoking is closely related to the occurrence of lung cancer. Cancer cells release special compounds that cause changes in the composition of people's exhaled air. Usually, the content of VOCs in the exhaled gas of lung cancer patients is dozens or even hundreds of times that of normal people. Therefore, the qualitative or quantitative analysis of VOCs gas through breath detection is helpful for the diagnosis of early lung cancer. Researchers have made a lot of efforts to develop equipment for lung cancer ...

AI Technical Summary

Problems solved by technology

However, there is no proven method for the detection of respiratory lung cancer in the early

In addition, existing technologies generally have shortcomings such as large errors, low sensitivity, and low reliability.

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