Heart rate, respiratory rate and airflow variability differences between stable and exacerbating chronic obstructive pulmonary disease patients

Rationale: Earlier identification and treatment of chronic obstructive pulmonary disease exacerbations leads to improved clinical outcomes. Wearable technology has the ability to measure physiological signal variability which is likely to be different in states of stability and exacerbation. // Objectives: To analyse signals including heart rate, respiratory rate and airflow, from a novel small wearable device, AcuPebble RE100 and compare differences in a group of stable and exacerbating participants. // Methods: Groups of stable and exacerbating adult participants with chronic obstructive pulmonary disease were asked to wear AcuPebble RE100, which records physiological signals including heart rate, respiratory rate and airflow. Linear and non-linear variability analysis was conducted on each of these time-series to detect differences between groups. // Results: A total of 51 participants (33 stable and 18 exacerbating) were analysed. Stable participants used the device for a median (IQR) of 18 nights (10–26). The exacerbating participants had significantly higher heart rate variability measures and a significantly lower heart rate complexity measure compared to stable participants. Respiratory rate variability and complexity were significantly increased in the exacerbating participants. Detrended fluctuation analysis demonstrated two-cross over points in both populations, with the exacerbating participants demonstrating a significantly lower median α3 (0.50 (0.47–0.56) versus 0.69 (0.65–0.79), p <0.001) compared to the stable population. // Conclusion: We have shown that significant differences exist in heart rate, respiratory rate and airflow variability measures between stable and exacerbating groups of chronic obstructive pulmonary disease. This will help build exacerbation detection algorithms in the future.