A detection event processing method

Abstract

The invention discloses a detection event processing method which is applicable to the medical field. The method comprises the following steps: receiving a multi-dimensional detection signal and decomposing the signal into corresponding sub-signals; according to the types of detection events, selecting sub-events of different dimensions and dividing corresponding types of the sub-signals in term of the detection signals; according to a reference sub-signal, carrying out interval partitioning on the sub-events of the same type; judging the credibility of multiple sub-events randomly selected from a preset interval so as to judge the credibility of the entire interval; judging whether the proportion of credible intervals under the same type reaches a preset threshold or not, if so, reserving all sub-events under the type and displaying the waveform of the sub-events, if not, discarding all sub-events under the type; and finally, displaying the waveform of the reserved sub-events. The technical scheme has the following beneficial effects: the method provides convenience for analyzers to process patient information, thereby shortening the time of analyzing and processing; and the method provides convenience for unifying the analysis standard of the analyzers and is capable of improving the analysis precision of the patient information.

Description

technical field [0001] The present invention relates to the technical field of medical event processing, in particular to a detection event processing method. Background technique [0002] In the prior art, a medical event can be defined as, but not limited to: an abnormal state of a living body with a certain duration and clinical or health significance. For example, atrial fibrillation events, fainting events, myocardial infarction events, sleep-disordered breathing events, etc. [0003] In the prior art, processes such as data acquisition and data processing of medical events usually require manual operations and processing one by one. Since medical data involves all aspects of human health information, such as human heartbeat fluctuations, atrial fibrillation fluctuations, heart rhythm, and the user's exercise status during the test, the amount of medical data is relatively large. In the existing technology, due to the limitation of the huge amount of medical data, the...

AI Technical Summary

Problems solved by technology

Even so, when analyzing the collected patient data, analysts or physicians still face the problem of huge and complicated data, and need to find out the data suitable for this detection event in a large number of medical data, and further Analysis and observation, the above-mentioned process is time-consuming and laborious, which prolongs the analysis time of the doctor's diagnosis and increases the difficulty of the doctor's diagnosis

To sum up, with the development of science and technology and the application of wearable and micro-sensors, although the problem of obtaining long-term continuous vital sign data can be partially solved, at the same time there is a huge demand for efficient and accurate intelligent information processing. The existing technologies cannot deal with the calculation and analysis problems brought about by such a large amount of messy data.

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