Measuring Uncertainty During Respiratory Rate Estimation Using Pressure-Sensitive Mats

• Published in: IEEE transactions on instrumentation and measurement Vol. 67; no. 7; pp. 1535 - 1542
• Main Authors: Nizami, Shermeen, Bekele, Amente, Hozayen, Mohamed, Greenwood, Kimberley J., Harrold, JoAnn, Green, James R.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Breathing rate; Computer simulation; confidence interval; Confidence intervals; continuous patient monitoring; creep; data analytics; Drift; Estimation; frequency domain; Frequency-domain analysis; intensive care; limits of agreement (LoA); Mats; Measurement uncertainty; mixed effects method; Monitoring; movement; neonatal; Parameter estimation; Parameter uncertainty; Pediatrics; pressure-sensitive mat (PSM); Respiratory rate; respiratory rate (RR); simulator; Systematics; Uncertainty; uncertainty measurements
• DOI: 10.1109/TIM.2018.2805154
• ISSN: 0018-9456

We develop and evaluate a respiratory rate (RR) estimation algorithm that utilizes data from the pressure-sensitive mat (PSM) technology for continuous patient monitoring in neonatal intensive care units. 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 the 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.