Filtering method and device for ventilator

Abstract

The invention discloses a filtering method for a ventilator, comprising: acquiring original data output by a sensor of the ventilator; using a method of N-fold burr processing to perform burr processing on the original data to obtain intermediate data; and adopting a method of weighted filtering Filtering the intermediate data to obtain filtered data of the sensor; wherein, N is a positive integer. First, burr processing is performed on the data output by the sensor, which can filter out the data fluctuations collected by the ventilator sensor with great efficiency. The weighted filtering method is used for the data after burr processing, which reduces the large error caused by pure arithmetic mean. question. In addition, the invention also discloses a filtering device for a ventilator.

Description

technical field [0001] The present invention relates to the field of electronic technology, in particular to a filtering method and device for a ventilator Background technique [0002] The ventilator adjusts one or more fluid parameters of the pressurized flow of breathing gas according to the treatment plan, which needs to be based on the flow data of the pressurized flow. The flow sensor is an important hardware device for collecting flow data, and the accuracy of its output data has a very important impact on the gas adjustment of the ventilator. [0003] The ventilator adjusts one or more fluid parameters of the pressurized flow of breathing gas according to the treatment plan, which needs to be based on the flow data of the pressurized flow. The flow sensor is an important hardware device for collecting flow data, and the accuracy of its output data has a very important impact on the gas adjustment of the ventilator. [0004] At present, filtering the output data of ...

AI Technical Summary

Problems solved by technology

This filter processing method uses clipping and recursive average processing methods. In the clipping process, due to the need to eliminate data with excessive amplitudes, it is easy to cause the sudden increase data caused by the subject's normal breathing to be filtered out as interference data. , In addition, different data have different influence weights in the entire output data. Therefore, if the recursive averaging process is used, the weight influence of a single data on the overall data is not considered, resulting in an excessive deviation between the filtered output data and the actual output data. low precision

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