Estimation of Respiration Rate using an Inertial Measurement Unit Placed on Thorax-Abdomen

Abstract

Respiration rate is one of the important measures of any physiological changes in human body. In this paper, an inertial measurement unit (IMU) is used to detect the chest movement and estimate the respiration rate from the real-time signal. A commercial inertial motion sensor chip used in this study that produces linear motion vector as streaming data. The signal from the motion sensor was sampled at 10 Hz. Signal processing was applied to denoise respiration signals from the values of linear motion vectors. Then, an algorithm of calculating respiration rate, was used to estimate breath per minute (BPM). The results were compared with a commercial respiration monitor belt logger sensor as the ground truth. The IMU sensor was tested at 5 different BPMs (12, 15, 20, 24, and 30) to validate the data from the IMU sensor and from the commercial respiration belt using a protocol where different BPM was maintained. The results show high accuracy of the proposed system which is simpler to use, cheaper to protype, and can be integrated with a wearable device and a custom smartphone app using edge computing technique.