Comparing time and frequency domain estimation of neonatal respiratory rate using pressure-sensitive mats

TL;DR

This study compares time and frequency domain methods for estimating neonatal respiratory rate using pressure-sensitive mats, finding frequency domain analysis provides superior accuracy with zero percent error.

Contribution

It demonstrates the effectiveness of frequency domain analysis of PSM data for neonatal RR estimation, a novel application in infant monitoring.

Findings

Frequency domain analysis achieves zero percent error in RR estimation.

Frequency domain outperforms time domain analysis in accuracy.

Peak height in periodogram provides a confidence measure.

Abstract

Pressure-sensitive mats (PSM) have proved to be useful in the estimation of respiratory rates (RR) in adult patients. However, PSM technology has not been extensively applied to derive physiologic parameters in infant and neonatal patients. This research evaluates the applicability of the capacitive XSensor PSM technology to estimate a range of RR in neonatal patient simulator trials conducted under several experimental conditions. PSM data are analyzed in both the time and frequency domain and comparative results are presented. For the frequency-domain approach, in addition to estimating RR, a measure of confidence is also derived from the relative height of peaks in the periodogram. The study demonstrates that frequency domain analysis of mean-shifted PSM data achieves the best possible RR estimation, with zero percent error, as compared to the lowest achievable RMS error of 1.57 percent in the time domain. The frequency domain approach outperforms the time domain analysis whether examining raw data or those preprocessed by normalizing, detrending and median filtering.