Physiological state recognition method

Abstract

The invention relates to a personnel physiological state recognition platform based on race detection. The recognition platform comprises a blood sugar monitoring sub-system, a brain wave monitoring sub-system, a race detection sub-system and an ARM11 processing chip. The blood sugar monitoring sub-system extracts blood sugar parameters of tested personnel on the basis of the detection result of the race detection sub-system. The brain wave monitoring sub-system monitors the brain wave states of the tested personnel. The ARM11 processing chip recognizes the physiological states of the tested personnel on the basis of the monitoring results of the blood sugar monitoring sub-system and the brain wave monitoring sub-system. By means of the personnel physiological state recognition platform, intelligent medical care monitoring can be provided for the tested personnel on the basis of race recognition.

Description

technical field [0001] The invention relates to the field of physiological parameter detection, in particular to a physiological state recognition method. Background technique [0002] At present, various physiological parameter detection instruments have the following defects: the detection mechanism is single, and each instrument is generally only used to detect one physiological parameter; the detection mechanism is backward, the structure redundancy of the detection instrument is not high, and the accuracy is not accurate enough; There are four races of test personnel. Due to the accumulation of history and the asynchrony of evolution, the warning thresholds of the physiological parameters of each race are different. The existing technology lacks intelligent detection methods based on race detection, which leads to The deviation is large. [0003] In the prior art, there is no equipment and mechanism that can solve the above technical problems at the same time, especial...

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Problems solved by technology

[0002] At present, various physiological parameter detection instruments have the following defects: the detection mechanism is single, and each instrument is generally only used to detect one physiological parameter; the detection mechanism is backward, the structure redundancy of the detection instrument is not high, and the accuracy is not accurate enough; There are four races of test personnel. Due to the accumulation of history and the asynchrony of evolution, the warning thresholds of the physiological parameters of each race are different. The existing technology lacks intelligent detection methods based on race detection, which leads to large deviation

[0003] In the prior art, there is no equipment and mechanism that can solve the above technical problems at the same time, especially in the aspect of race recognition, it is even impossible to use artificial naked eyes for recognition, select different threshold parameters according to the recognition results, let alone use machine automatic way to identify

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