Validation of a wearable device and an algorithm for respiratory monitoring during exercise

This paper investigates the performances of a headmountedwearable device for the breath-by-breath monitoring ofrespiratory frequency (f R) during exercise. The device exploitsa new algorithm to estimate f R from the breathing-relatedpressure drops (P) recorded at the nostrils level. Performancesof the wearable device in measuring the breath-by-breath and30-s average f R values were evaluated during two high-intensitycycling exercise tests performed in the laboratory. P signalswere collected from ten volunteers with the wearable device,and the simultaneous measurements with a reference instrumentwere performed for validation purposes. In addition, numericalsimulations were carried out to reproduce the conditions expectedin applied settings. Bland–Altman analysis, linear regression (r2),and percentage error (%E) were used for comparing thetwo instruments. Experimental tests demonstrate the robustnessand validity of the proposed wearable device and therelated algorithm to measure the breath-by-breath f R (overall%E = 4.03%) and 30-s average f R (overall %E = 2.38%)values. Biases obtained with the breath-by-breath analysis (max.−0.06 ± 6.27 breaths/min) were higher than those obtained in the30-s window analysis (max. −0.03 ± 1.60 breaths/min). In thesimulated conditions, %E increased up to 6.65%. The proposedwearable device is suitable for a wide variety of indoor applicationswhere the fR monitoring during exercise at reducedinvasiveness is of great value.