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

Paul S. Addison,Cyndy Miller,Dominique Jacquel,Anthony P. Addison,Gardner Kimm,Philip Smit

doi:10.1007/s10877-021-00691-3

Abstract

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 (RRdepth) and tidal volume (TVdepth) estimates. The bias and root mean squared difference (RMSD) accuracy between RRdepth and the ventilator reference, RRvent, 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: RRdepth = 0.96 × RRvent + 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 TVdepth and the reference TVvent 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: TVdepth = 0.79 × TVvent—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 RRdepth 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 TVdepth may provide a useful monitor of tidal volume trending in practice. Future work should aim to further test these parameters in the clinical setting.

Highlights

The measurement of respiratory function is important in the hospital setting as it relates to numerous disease states and may be indicative of ensuing issues
A Pearson correlation coefficient of 0.98 (p < 0.001) was achieved and a line of best fit given by R Rdepth = 0.96 × RRvent + 0.57 breaths/min
A Pearson correlation coefficient of 0.92 (p < 0.001) was achieved together with a line of best fit given by TVdepth = 0.79 × TVvent—0.01 L

Summary

Introduction

The measurement of respiratory function is important in the hospital setting as it relates to numerous disease states and may be indicative of ensuing issues. Depth cameras are emerging as a tool that can provide a continuous measure of both respiratory rate and tidal volume. They do so by first deriving a respiratory volume (RV) signal from the respiratory motions of the patient from which these parameters can be extracted. The non-contact monitoring of RR and TV would prove valuable in the monitoring of viral pandemics, including novel coronavirus (COVID-19) patients, as well as those with other viral respiratory tract diseases, where minimum contact with the patient is desired and a robust measurement is essential [6, 7]

Methods

Results

Discussion

Conclusion