Remote diabetes intelligent diagnosis system based on electronic nose for detecting respiratory gas

Abstract

The invention relates to a remote diabetes intelligent diagnosis system based on electronic nose for detecting respiratory gas, which includes: an electronic nose detection module, a wireless transmission module, an intelligent mobile terminal module, and a machine learning application module deployed in a cloud platform. The system can remotely analyze expiration signal, collected by the electronic nose, of human body by using the machine learning application deployed in the cloud platform in order to obtain a diagnosis result, which is then sent to and displayed on the intelligent mobile terminal module. The electronic nose detection module can acquire concentration information of sensitive components in the respiratory gas from a user and then sends a responding signal to the intelligent mobile terminal module through the wireless transmission module; then the user uploads the data to a cloud server for processing the data; and the machine learning application deployed in the cloudplatform can quickly give out the diagnosis result, which is displayed on the intelligent mobile terminal module. The intelligent diagnosis system achieves rapid noninvasive diagnosis of diabetes, hasthe potential of supplying remote medical service, reduces use threshold of users, and may be applied to large-scale screening and daily detection on the diabetes.

Description

technical field [0001] The invention relates to the field of disease diagnosis, and specifically proposes a remote diabetes intelligent diagnosis system based on electronic nose detection of breathing gas, which is expected to be used for remote and non-invasive diagnosis of diabetes. Background technique [0002] In recent years, the number of diabetic patients has been increasing worldwide, especially in developing countries. Studies have found that early diagnosis of diabetes is of great significance. At present, conventional diagnostic methods are mainly based on blood glucose, and this invasive diagnostic method will bring a lot of pain and heavy psychological burden to the subjects. Studies in recent years have shown that normal people and diabetic patients can be effectively distinguished by detecting the content of certain gas components in the exhaled breath of the human body. Among the current breath detection equipment, the electronic nose can respond to various ...

AI Technical Summary

Problems solved by technology

[0003] However, there are still many problems to be solved in this field. Although the existing electronic nose systems can perform non-invasive diagnosis of diabetes, these systems need to rely on the local host computer for pattern recognition.

The local host computer is expensive, which is not only a huge waste of hardware resources, but also greatly increases user costs and raises the threshold for users to use, making it difficult for the system to be popularized in the vast communities and hospitals at all levels, which is not conducive to the system's large-scale Crowd screening and routine testing

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