Non-Contact Infrared-Depth Camera-Based Method for Respiratory Rhythm Measurement While Driving

This work proposes a new non-contact method based on Infrared and Depth cameras to measure respiratory rhythm in real-life situations. The proposed algorithm consists on using both video feeds to track the movements of the subject in real-time, compute the location of the face and calculate the most suitable ROI to extract the respiratory signal in adult population. 20 subjects were measured while driving in a car simulator with no constraints other than the simulator itself. The algorithm has been validated using a commercial thorax plethysmography system. An opportunistic approach has been used to obtain pieces from the tests for each subject, thus making a more realistic approach to the real-life situations where the signal is likely to contain errors. The breath-to-breath respiratory signal and the instantaneous frequency from both methods has been computed from each piece to characterise the error between the proposed method and the reference system. The results show a high correlation between the measured rhythm from the reference method and the proposed method, with relatively low error results and good sensitivity in cycle detection and low errors for the instantaneous frequency between methods. The error results have also been compared with the ones obtained in previous studies showing a good agreement between the obtained results and the ones presented in the previous studies. No relationship between the length of the pieces and the error has been found either for the respiratory cycle signal or the instantaneous frequency signal. The proposed algorithm can be used to measure respiratory rhythm in unconstrained conditions and with opportunistic measurements, thus making it suitable to perform in real-life situations while driving. Further studies taking into account vibrations or light changing conditions are needed to confirm that the proposed method performs with the same accuracy with these constraints.