Efficient video-based breathing pattern and respiration rate monitoring for remote health monitoring

Abstract

A contact-free inexpensive measurement system with an algorithm based on the integral form of video frames is proposed to estimate the respiration rate from an extracted respiration pattern. The proposed algorithm is applied and tested on 28 videos of sleeping-simulated positions, and the results are compared with the manual visual inspection values. With linear regression, the determination coefficient (<i>R</i>²) is 0.961, which demonstrates high agreement with reference measurements. In addition, the Bland-Altman plot shows that almost all data points are within the 95% limits of agreement. Moreover, the time complexity of the proposed algorithm, which involves taking just a single point value of the integral image, is lower than that of traditional methods that circulate over a large number of points. In other words, the proposed algorithm achieves <i>O</i>(1) fixed-time complexity compared to <i>O</i>(<i>N</i>²) for traditional methods. The average speed of processing is enhanced by about 17.4%.