IMU-Based Respiratory Signal Processing Using Cascade Complementary Filter Method

Abstract

The purpose of this paper is to propose a cascade complementary filter (CCF) for tracking abdominal or diaphragmatic movement induced by respiratory activity. An inertial sensor (3 DOF accelerometer and 3 DOF gyroscope) is mounted on the upper abdomen, allowing the tilt value of the upper abdomen to be measured. CCF is aimed at overcoming the limitations of the linear CF method for online gyroscope estimation. Our proposed CCF algorithm compensates gyroscope bias with a nonlinear filter and then fuses it with accelerometer angle to obtain abdominal inclination. The CCF method performed better than the linear CF method in terms of respiratory rate error. While CCF increased estimation accuracy, it also appeared to be independent of attitude estimation parameters. The frequency of the CCF respiratory signal remained steady between 0.2 Hz and 0.4 Hz throughout the experiment, with a mean of 0.29 Hz. In other words, the results range between 12 and 24 breaths per minute, which is considered normal at 17 breaths per minute.