Measuring uncertainty during respiratory rate estimation using pressure-sensitive mats

TL;DR

This paper presents a novel algorithm using pressure-sensitive mats for continuous neonatal respiratory rate monitoring, analyzing uncertainty factors and demonstrating clinical accuracy within acceptable limits.

Contribution

The study introduces a new PSM-based respiratory rate estimation method and evaluates its uncertainty, showing it meets clinical accuracy standards in neonatal care.

Findings

Mean bias of 0.56 bpm compared to gold standard

Error bounds within [-2.26, 3.37] bpm at 95% confidence

Achieves clinical accuracy within +/-5 bpm

Abstract

We develop and evaluate a respiratory rate estimation algorithm that utilizes data from pressure-sensitive mat (PSM) technology for continuous patient monitoring in neonatal intensive care units (NICU). An analysis of the random effect of drift and systematic effect of creep in the PSM data is presented, showing that these are essentially dependent on the applied load and contact surface. Uncertainty measurements are pivotal when estimating physiologic parameters. The standard uncertainty in the PSM data is here represented by the percent drift. Next, we evaluate the applicability of PSM technology to estimate RR in neonatal patient simulator trials under five mixed effects including internally and externally induced motion, mattress type, grunting, laying position, and different breathing rates. We analyze the limits of agreement on the mixed effects model to derive the uncertainty in the estimated RR obtained through two estimation techniques. In comparison with the gold standard RR values, we achieved a mean bias of 0.56 breaths per minute (bpm) with an error bounded by a 95% confidence interval of [-2.26, 3.37] bpm. These results meet the clinical accuracy requirements of RR within +/-5 bpm.