用力肺活量（FVC）是肺功能评估的关键指标，广泛应用于慢性阻塞性肺疾病（COPD）等呼吸疾病的早期筛查。实践中呼气时间过短是导致测得FVC偏低的主要原因。前期工作中我们研制出高精度、大量程的肺功能仪，并成功应用于肺功能检测。本项目提出一种基于系统辨识的呼吸信号分析方法，旨在降低肺功能检测对呼气时间的要求。具体思路是：通过对用力呼气的生理特征解析与实验研究，构建并验证一个包含FVC参数的用力呼气数学模型；研究基于系统辨识方法估计FVC精度与选取观测曲线长度的关系，确定最短可观测曲线的时间长度，以降低传统肺功能检测对用力呼气时间的要求；基于系统辨识估计呼气时间过短曲线的FVC研究，解决因受试者呼气时间过短而无法准确评估肺功能的问题。本项目旨在将信号分析方法应用于肺功能检测以降低其测试难度，进而有助于肺功能检查的临床应用和推广，在COPD防治领域具有重要应用价值。

Forced vital capacity (FVC) is a key indicator to evaluate pulmonary function, and it is also widely used in the screen of respiratory diseases, such as chronic obstructive pulmonary disease (COPD). The short time of expiration is the main reason of the low quality of pulmonary function tests and the underestimation of FVC in practice. In previous study, we developed a pulmonary function instrument with high precision, a large range, and successfully applied to the lung function testing. In this study, we propose a novel method for analyzing forced expiratory signals using system identification to reduce the requirement of forced expiratory time. In order to address this comprehensively, we will conduct the following works. First, we establish and validate a forced expiratory mathematical model, of which FVC is one parameter. The establishment and the validation of the forced expiratory mathematical model is based on the analysis of the physiological characteristics and pulmonary function testing data. Then, we will investigate the relationship between the accuracy of estimated FVC by using system identification and the length of the observed curve, and determine the shortest time length of the observable curve, which would reduce the requirement of he forced expiratory time in pulmonary function testing. Finally, we apply this method to the unacceptable forced expiratory curves because of short expiratory time, and solve the problem of incorrectly assessing pulmonary function caused by the high requirement of expiratory time. The aim of the present study is to reduce the difficulty of testing by applying the method of analyzing forced expiratory signals to the pulmonary function testing, and contribute to the clinical application and promotion of the pulmonary function testing, which have important application prospect in the field of prevention and cure of COPD.