# Thermal Cameras for Overnight Measuring of Respiration in a Clinical Setting

## TL;DR

Thermal cameras can accurately monitor breathing during sleep, offering a non-contact alternative to traditional methods.

## Contribution

This study is the first to evaluate thermal cameras for respiration monitoring in a clinical sleep setting.

## Key findings

- Thermal cameras achieved 96.3% sensitivity and 94.1% precision in breath detection.
- Respiration rate estimates had a mean absolute error of 0.64 to 0.91 breaths per minute.
- Using multiple or a single thermal camera showed no significant difference in results.

## Abstract

Thermal imaging is a non-contact method for monitoring respiration activity during sleep. In this study, we evaluated its clinical application during overnight recordings in a sleep clinic. Five thermal cameras were used to detect breaths, the estimated respiration rate (RR), and inter-breath intervals (IBIs) in seven adults undergoing diagnostic polysomnography (PSG). Forty-five minutes of recordings were selected, consisting of 12 motionless and event-free segments. The thermal videos were processed using an adapted pre-existing thermal video processing algorithm. The respiration signals generated with the thermal cameras were validated against simultaneously recorded signals from the PSG system, the current gold standard for monitoring sleep. The results show a mean absolute error (MAE) ranging between 0.64 and 0.91 breaths per minute for the RR. Breath detection showed a sensitivity of 96.3%, and a precision of 94.1%. The MAE obtained between IBIs was 0.48 s, and the mean IBI variability difference recorded was 3.9 percentage points. In addition, the results from this clinical study show that the use of all five cameras and a single camera revealed no statistically significant differences, demonstrating the work towards a robust system. This first study of thermal cameras for the assessment of respiration in a clinical setting shows us the potential application of thermal imaging in clinical practice for respiration monitoring and establishes a foundation for further implementation in assessing sleep-disordered breathing.