Abstract
Cough is a respiratory protective behavior for clearing the secretion. The cough process can be characterized by three features which are cough peak flow rate, peak velocity time, and cough expired volume. The cough expired volume (CEV) and the cough peak flow rate (CPFR) are important for medical diagnosis and cough effectiveness assessment. In this study, the CEV and CPFR values of 700 healthy participants were measured and collected by using a portable pulmonary function device. The gender, age, height, weight, and smoking status information of the 700 participants were also collected. Meanwhile, the integration of backpropagation neural network and genetic algorithm (GA-BP) method was developed to estimate CEV and CPFR values. The results showed that the estimation accuracy of GA-BP method exceeds 90%, which indicates that the GA-BP method could be effectively used for CEV and CPFR value estimation. Furthermore, the method proposed in this paper could be useful for medical diagnosis and medical device development.
Highlights
Cough is a kind of respiratory reflex behavior
The cough process continued about 0.4∼0.6 s and can be characterized by three parameters which are cough peak flow rate (CPFR), peak velocity time (PVT), and cough expired volume (CEV) [7,8,9,10]. e CEV and CPFR are the total exhausted air volume and the maximum airflow rate measured in atmosphere normal reference during the whole cough process, respectively
As for the patients with mechanical ventilation, neuromuscular disease, or other diseases which impairs the cough ability, the CEV and CPFR values cannot be obtained and used for medical diagnosis. erefore, establishing a relationship between the CEV, CPFR values and human physical information could be used for medical diagnosis for these patients
Summary
Shuai Ren ,1,2 Jinglong Niu ,3 Zihao Luo ,1 Yan Shi ,1 Maolin Cai, Zujin Luo ,4 and Qihui Yu 2. E cough process can be characterized by three features which are cough peak flow rate, peak velocity time, and cough expired volume. E cough expired volume (CEV) and the cough peak flow rate (CPFR) are important for medical diagnosis and cough effectiveness assessment. The CEV and CPFR values of 700 healthy participants were measured and collected by using a portable pulmonary function device. The integration of backpropagation neural network and genetic algorithm (GA-BP) method was developed to estimate CEV and CPFR values. E results showed that the estimation accuracy of GA-BP method exceeds 90%, which indicates that the GA-BP method could be effectively used for CEV and CPFR value estimation. The method proposed in this paper could be useful for medical diagnosis and medical device development
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