基于涡轮式气体流量传感器的用力呼气容量计算方法

Calculation of Forced Vital Capacity Based on Turbine Air Flow Sensor

涡轮式气体流量传感器在用力肺功能测试中用于记录人体呼气信号,由于旋转惯性,对于相同用力呼气容量(FVC)值,测量结果因呼出气体流量而异,且差异值通常不可接受。针对该问题,该文通过在传统稳态涡轮流量计算模型的基础上引入速度惩罚项,构建一种FVC速度惩罚模型,与此同时,提出使用过幅降采样涡轮旋转周数算法,二者结合,提高了FVC测试结果的可接受性。利用国际通用的标准3 L定标桶,模拟真实用力肺功能测试过程,对算法的有效性进行验证。实验结果表明:所提方法能够有效降低前述差异,在一定程度上满足美国胸科协会(ATS)和欧洲呼吸学会(ERS)所提出的用力肺功能测试可接受标准和准确度要求。

Currently,the turbine air flow sensors are widely used to record the human exhalation signals in spirometry,but test results vary due to different expiratory flow for the same Forced Vital Capacity(FVC)measurements,and the differences are usually not in an acceptable range.To address this issue,a FVC velocity penalty model is proposed by introducing speed penalty items to the traditional mathematical model of turbine.Moreover,an over-amplitude drop sampling approach is used to calculate the rotations of the turbine due to the needs for the velocity penalty model to be able to accurately obtain the number of turbine rotations.The performance of the proposed approach is evaluated by using a syringe dispenser of 3L capacity,and results demonstrate that it can reduce the differences and meet the acceptable and accuracy criteria of the American Thoracic Society(ATS)and the European Respiratory Society(ERS)to some extent.