Continuous non-contact respiratory rate and tidal volume monitoring using a Depth Sensing Camera

The monitoring of respiratory parameters is important across many areas of care within the hospital. Here we report on the performance of a depth-sensing camera system for the continuous non-contact monitoring of Respiratory Rate (RR) and Tidal Volume (TV), where these parameters were compared to a ventilator reference. Depth sensing data streams were acquired and processed over a series of runs on a single volunteer comprising a range of respiratory rates and tidal volumes to generate depth-based respiratory rate (RR_depth) and tidal volume (TV_depth) estimates. The bias and root mean squared difference (RMSD) accuracy between RR_depth and the ventilator reference, RR_vent, across the whole data set was found to be -0.02 breaths/min and 0.51 breaths/min respectively. The least squares fit regression equation was determined to be: RR_depth = 0.96 × RR_vent + 0.57 breaths/min and the resulting Pearson correlation coefficient, R, was 0.98 (p < 0.001). Correspondingly, the bias and root mean squared difference (RMSD) accuracy between TV_depth and the reference TV_vent across the whole data set was found to be - 0.21 L and 0.23 L respectively. The least squares fit regression equation was determined to be: TV_depth = 0.79 × TV_vent-0.01 L and the resulting Pearson correlation coefficient, R, was 0.92 (p < 0.001). In conclusion, a high degree of agreement was found between the depth-based respiration rate and its ventilator reference, indicating that RR_depth is a promising modality for the accurate non-contact respiratory rate monitoring in the clinical setting. In addition, a high degree of correlation between depth-based tidal volume and its ventilator reference was found, indicating that TV_depth may provide a useful monitor of tidal volume trending in practice. Future work should aim to further test these parameters in the clinical setting.