Reliable Respiratory Rate Estimation from a Bed Pressure Array

Unobtrusive sleep monitoring allows older adults to have continuous monitoring during the night in their own homes. We propose a method to reliably estimate respiratory rate using a bed-based pressure sensor array. Movements are detected prior to respiratory rate estimation and suppressed. The amount of movement during an estimate and a weighting for the estimate are used to create a reliability metric. The reliability metric is scored out of 100 for each sensor where high scores denote more reliable data. Once respiratory rates were calculated, the mean reliability metric determined the estimate reliability. Nocturnal data from a male and female participant was analyzed. Results show better accuracy and validity than both analysis without movement suppression and analysis with movement suppression but without postprocessing data fusion. While more than 50% of estimates include movement corruption, only 15% are unreliable and, moreover, removal of unreliable estimates significantly reduces estimate variance and provides validity estimation