This work proposes a new method based on computer vision algorithms to measure the respiratory rhythm of a subject from a lateral perspective. The proposed algorithm consists on tracking the motion of the intercostal and abdominal muscles by the means of dense optical flow, being the novelty of the proposed method the extraction of the respiratory signal from the phase of the optical flow, while extracting at the same time a quality index from the modulus. 15 healthy subjects were measured while seating, and 4 tests were performed for each subject involving different scenarios. The algorithm has been validated using a commercial wearable thorax inductive plethysmograph system. The instantaneous frequency for the constant frequency respiratory tests, and the breath to breath analysis and instantaneous frequency of the free breathing test have been computed to assess the performance and error of the proposed method for the respiratory acquisition. Finally, a statistical analysis has been performed to assess the accuracy and performance of the quality index. The results of the study show a high agreement between methods in the 0.1 Hz and 0.3 Hz test. For the Free breathing test, both the cycle by cycle and Instantaneous frequency results show a low error between methods with high sensitivity in the cycle detection. The hypothesis that the modulus of the optical flow could be used as a quality index has been corroborated, with very good statistical results. Moreover, due to the simplicity of the proposed algorithm, the proposed method can perform in real-time while measuring respiratory rhythm and assessing the quality of the acquired signal. Further studies taking into account external vibrations have to be performed, to assert that the proposed method can be used in demanding conditions.

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The aim of this work is to characterize the differences in the respiratory rhythm obtained through three video based methods by comparing the obtained respiratory signals with the one obtained with the gold standard method in adult population. The analysed methods are an RGB camera, a depth camera and a thermal camera while the gold standard is an inductive thorax plethysmography system (Respiband system from BioSignals Plux).21 healthy subjects where measured, performing 4 tests for each subject. The respiratory rhythm and its variability was obtained from the four respiratory signals (3 video methods and gold standard). The signal acquisition was performed with custom and proprietary algorithms. To characterize the respiratory rhythm and its variability obtained with the different video sources and gold standard, the instantaneous frequency, Bland-Altman plots and standard deviation of the error between video methods and the gold standard have been computed.The depth and RGB camera present high agreement with no statistical differences between them, with errors when comparing with the gold standard in the range of mHz. The thermal camera performs poorly if compared with the two other methods, nevertheless it cannot be discarded directly because some errors produced by the subjects head movement could not be corrected.From these results we conclude that the depth and RGB camera, and their respective acquisition algorithms, can be used in controlled conditions to measure respiration rhythm and its variability. The thermal camera on the other hand, although it can not be discarded directly, performed poorly if compared with the other two methods. Further studies are needed to confirm that these methods can be used in real life conditions.

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