Estimation of respiratory rate using infrared video in an inpatient population: an observational study

This study utilized infrared thermography (IRT) to measure RR in a critically ill population in the Intensive Care Unit. This study was carried out in a Single Hospital Centre. Respiratory rate in 27 extubated ICU patients was counted by two observers and compared to ECG Bioimpedance and IRT-derived RR at distances of 0.4 –0.6 m and>  1 m respectively. IRT-derived RR using two separate computer vision algorithms outperformed ECG derived RR at distances of 0.4–0.6 m. Using an Autocorrelation estimator, mean bias was − 0.667 breaths/min. Using a Fast Fourier Transform estimator, mean bias was − 1.000 breaths/min. At distances greater than 1 m no statistically significant signal could be obtained. Over all frequencies, there was a significant relationship between the RR estimated using IRT and via manual counting, with Pearson correlation coefficients between 0.796 and 0.943 (p <  0.001). Correlation between counting and ECG-derived RR demonstrated significance only at>  19 bpm (r = 0.562, p = 0.029). Overall agreement between IRT-derived RR at distances of 0.4–0.6 m and gold standard counting was satisfactory, and outperformed ECG derived bioimpedance. Contactless IRT derived RR may be feasible as a routine monitoring modality in wards and subacute i npatient settings.
Source: Journal of Clinical Monitoring and Computing - Category: Information Technology Source Type: research