A high-accuracy calibration-free spirometer based on Fiber Bragg Grating technique with neural network optimization

Chronic respiratory diseases as one of the major global health problems induce a high mortality rate. Increasing needs raised from domestic healthcare require the development of new spirometers with the combination of multiple features, e.g. low cost, light weight, high accuracy, easy to use, high reliability and long service life. Fiber Bragg Grating (FBG) technique outstands for spirometry due to its unique advantages. This study presents a novel FBG spirometer providing a high accuracy in vital capacity measurement (an average prediction error of 2.79 % for 37 volunteers), without the necessity of separate calibration of the system with the assistance of neural network. This FBG spirometer is easy to use and fast to analyze, moreover, it can be developed for more clinic and domestic applications like respiratory monitoring and the diagnosis of lung diseases based on the dynamic analysis of exhalation. • A portable spirometer based on the Fiber Bragg Grating (FBG) technique is developed. • This FBG spirometer presents high accuracy, with an average prediction error as low as 2.79 % for 37 volunteers. • This FBG spirometer does'nt require any form of calibration for the measurement of vital capacity. • A feed-forward neural network model is adopted for the prediction of vital capacity.