Continuous respiratory rate monitoring during an acute hypoxic challenge using a depth sensing camera

Paul S Addison,Ulf R Borg,Dominique Jacquel,Philip Smit

doi:10.1007/s10877-019-00417-6

Paul S Addison, Ulf R Borg + Show 2 more

Open Access

https://doi.org/10.1007/s10877-019-00417-6

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Abstract

Respiratory rate is a well-known to be a clinically important parameter with numerous clinical uses including the assessment of disease state and the prediction of deterioration. It is frequently monitored using simple spot checks where reporting is intermittent and often prone to error. We report here on an algorithm to determine respiratory rate continuously and robustly using a non-contact method based on depth sensing camera technology. The respiratory rate of 14 healthy volunteers was studied during an acute hypoxic challenge where blood oxygen saturation was reduced in steps to a target 70% oxygen saturation and which elicited a wide range of respiratory rates. Depth sensing data streams were acquired and processed to generate a respiratory rate (RRdepth). This was compared to a reference respiratory rate determined from a capnograph (RRcap). The bias and root mean squared difference (RMSD) accuracy between RRdepth and the reference RRcap was found to be 0.04 bpm and 0.66 bpm respectively. The least squares fit regression equation was determined to be: RRdepth = 0.99 × RRcap + 0.13 and the resulting Pearson correlation coefficient, R, was 0.99 (p < 0.001). These results were achieved with a 100% reporting uptime. In conclusion, excellent agreement was found between RRdepth and RRcap. Further work should include a larger cohort combined with a protocol to further test algorithmic performance in the face of motion and interference typical of that experienced in the clinical setting.

Highlights

The clinical importance of respiratory rate (RR) is well known as it provides important information regarding many aspects of a patient’s respiratory status
A wide range of methods have been proposed for the determination of respiratory rate using non-contact means including RGB video camera systems [4, 5], infrared camera systems [6], laser vibrometry [7], piezoelectric bed sensors [8], doppler radar
Many studies have compared tidal volume, as measured by a reference system, with the tidal volume extracted by a depth camera system based on morphological changes in the chest wall

Summary

Introduction

The clinical importance of respiratory rate (RR) is well known as it provides important information regarding many aspects of a patient’s respiratory status. One of the earliest tidal volume measurements extracted in this way was carried out by Yu et al [12] They assessed a Kinect V1 based system against a spirometer and achieved a correlation coefficient, R = 0.97 (p < 0.001), based on 12 healthy subjects undertaking a range or respiratory activities including shallow, middle and deep breathing as well as isovolume maneuvers. Martinez and Stiefelhagen [21] utilised a depth camera to extract respiratory rate data from 94 sleep analysis sessions from 67 patients in a sleep clinic They found their system to be 85.9% accurate when compared to a reference thermistor placed at the nose. The work reported here extends current research in this area by studying a cohort of healthy volunteers exhibiting a wide range of respiratory rates resulting from being subjected to a rigorous, protocolized hypoxic challenge

Clinical study

Data acquisition and processing

Results

Discussion

Compliance with ethical standards