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Related Concept Videos

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Updated: Jul 30, 2025

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Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals.

Naser Hakimi1,2, Mohammad Shahbakhti1, Jörn M Horschig1

  • 1Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The Netherlands.

Sensors (Basel, Switzerland)
|May 13, 2023
PubMed
Summary
This summary is machine-generated.

A new algorithm extracts respiratory rate (RR) from neonatal near-infrared spectroscopy (NIRS) signals. This innovation allows for simultaneous monitoring of cerebral hemodynamics and respiration in intensive care settings.

Keywords:
cerebral oxygenationnear-infrared spectroscopyneonatesrespiratory ratesignal quality assessment

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Area of Science:

  • Biomedical Engineering
  • Neonatal Physiology
  • Medical Signal Processing

Background:

  • Near-infrared spectroscopy (NIRS) signals are affected by physiological noise, including respiration and heart rate.
  • Simultaneous NIRS and respiratory rate (RR) monitoring is crucial for assessing neonatal cerebral physiology.
  • Current methods lack perfectly time-synced assessment of NIRS and RR in neonatal intensive care units (NICUs).

Purpose of the Study:

  • To develop and validate a novel algorithm for extracting respiratory rate (RR) from cerebral NIRS signals in neonates.
  • To enable simultaneous, time-synced assessment of cerebral hemodynamics and respiratory function using a single sensor.

Main Methods:

  • Development of the NIRS RR (NRR) algorithm to extract RR from NIRS intensity signals.
  • Synchronous recording of NIRS and reference RR signals from ten critically ill neonates in a NICU.
  • Performance evaluation based on agreement, linear correlation, and statistical comparison with existing methods.

Main Results:

  • The NRR algorithm demonstrated a mean error of 1.1 BPM and limits of agreement of 6.7 BPM.
  • A high linear correlation of 84.5% (p < 0.01) was achieved between NRR-extracted and reference RRs.
  • The NRR algorithm significantly outperformed two existing methods (p < 0.05).

Conclusions:

  • Respiratory rate can be reliably extracted from neonatal NIRS signals in an intensive care environment.
  • The NRR algorithm offers a novel approach for integrated monitoring of cerebral hemodynamics and respiration.
  • This enables concurrent analysis of respiratory impacts, such as apnea, on neonatal cerebral perfusion.