Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals
<i>Background:</i> Near-infrared spectroscopy (NIRS) relative concentration signals contain ‘noise’ from physiological processes such as respiration and heart rate. Simultaneous assessment of NIRS and respiratory rate (RR) using a single sensor would facilitate a perfectly time-synced as...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/9/4487 |
| _version_ | 1797601653103263744 |
|---|---|
| author | Naser Hakimi Mohammad Shahbakhti Jörn M. Horschig Thomas Alderliesten Frank Van Bel Willy N. J. M. Colier Jeroen Dudink |
| author_facet | Naser Hakimi Mohammad Shahbakhti Jörn M. Horschig Thomas Alderliesten Frank Van Bel Willy N. J. M. Colier Jeroen Dudink |
| author_sort | Naser Hakimi |
| collection | DOAJ |
| description | <i>Background:</i> Near-infrared spectroscopy (NIRS) relative concentration signals contain ‘noise’ from physiological processes such as respiration and heart rate. Simultaneous assessment of NIRS and respiratory rate (RR) using a single sensor would facilitate a perfectly time-synced assessment of (cerebral) physiology. Our aim was to extract respiratory rate from cerebral NIRS intensity signals in neonates admitted to a neonatal intensive care unit (NICU). <i>Methods:</i> A novel algorithm, NRR (NIRS RR), is developed for extracting RR from NIRS signals recorded from critically ill neonates. In total, 19 measurements were recorded from ten neonates admitted to the NICU with a gestational age and birth weight of 38 ± 5 weeks and 3092 ± 990 g, respectively. We synchronously recorded NIRS and reference RR signals sampled at 100 Hz and 0.5 Hz, respectively. The performance of the NRR algorithm is assessed in terms of the agreement and linear correlation between the reference and extracted RRs, and it is compared statistically with that of two existing methods. <i>Results:</i> The NRR algorithm showed a mean error of 1.1 breaths per minute (BPM), a root mean square error of 3.8 BPM, and Bland–Altman limits of agreement of 6.7 BPM averaged over all measurements. In addition, a linear correlation of 84.5% (<i>p</i> < 0.01) was achieved between the reference and extracted RRs. The statistical analyses confirmed the significant (<i>p</i> < 0.05) outperformance of the NRR algorithm with respect to the existing methods. <i>Conclusions:</i> We showed the possibility of extracting RR from neonatal NIRS in an intensive care environment, which showed high correspondence with the reference RR recorded. Adding the NRR algorithm to a NIRS system provides the opportunity to record synchronously different physiological sources of information about cerebral perfusion and respiration by a single monitoring system. This allows for a concurrent integrated analysis of the impact of breathing (including apnea) on cerebral hemodynamics. |
| first_indexed | 2024-03-11T04:06:40Z |
| format | Article |
| id | doaj.art-398c959d6a9a42ddafa952d565ff0654 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T04:06:40Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-398c959d6a9a42ddafa952d565ff06542023-11-17T23:45:05ZengMDPI AGSensors1424-82202023-05-01239448710.3390/s23094487Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy SignalsNaser Hakimi0Mohammad Shahbakhti1Jörn M. Horschig2Thomas Alderliesten3Frank Van Bel4Willy N. J. M. Colier5Jeroen Dudink6Artinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsDepartment of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The NetherlandsDepartment of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The NetherlandsArtinis Medical Systems, B.V., Einsteinweg 17, 6662 PW Elst, The NetherlandsDepartment of Neonatology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Lundlaan 6, 3584 EA Utrecht, The Netherlands<i>Background:</i> Near-infrared spectroscopy (NIRS) relative concentration signals contain ‘noise’ from physiological processes such as respiration and heart rate. Simultaneous assessment of NIRS and respiratory rate (RR) using a single sensor would facilitate a perfectly time-synced assessment of (cerebral) physiology. Our aim was to extract respiratory rate from cerebral NIRS intensity signals in neonates admitted to a neonatal intensive care unit (NICU). <i>Methods:</i> A novel algorithm, NRR (NIRS RR), is developed for extracting RR from NIRS signals recorded from critically ill neonates. In total, 19 measurements were recorded from ten neonates admitted to the NICU with a gestational age and birth weight of 38 ± 5 weeks and 3092 ± 990 g, respectively. We synchronously recorded NIRS and reference RR signals sampled at 100 Hz and 0.5 Hz, respectively. The performance of the NRR algorithm is assessed in terms of the agreement and linear correlation between the reference and extracted RRs, and it is compared statistically with that of two existing methods. <i>Results:</i> The NRR algorithm showed a mean error of 1.1 breaths per minute (BPM), a root mean square error of 3.8 BPM, and Bland–Altman limits of agreement of 6.7 BPM averaged over all measurements. In addition, a linear correlation of 84.5% (<i>p</i> < 0.01) was achieved between the reference and extracted RRs. The statistical analyses confirmed the significant (<i>p</i> < 0.05) outperformance of the NRR algorithm with respect to the existing methods. <i>Conclusions:</i> We showed the possibility of extracting RR from neonatal NIRS in an intensive care environment, which showed high correspondence with the reference RR recorded. Adding the NRR algorithm to a NIRS system provides the opportunity to record synchronously different physiological sources of information about cerebral perfusion and respiration by a single monitoring system. This allows for a concurrent integrated analysis of the impact of breathing (including apnea) on cerebral hemodynamics.https://www.mdpi.com/1424-8220/23/9/4487near-infrared spectroscopyneonatesrespiratory ratecerebral oxygenationsignal quality assessment |
| spellingShingle | Naser Hakimi Mohammad Shahbakhti Jörn M. Horschig Thomas Alderliesten Frank Van Bel Willy N. J. M. Colier Jeroen Dudink Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals Sensors near-infrared spectroscopy neonates respiratory rate cerebral oxygenation signal quality assessment |
| title | Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals |
| title_full | Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals |
| title_fullStr | Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals |
| title_full_unstemmed | Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals |
| title_short | Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals |
| title_sort | respiratory rate extraction from neonatal near infrared spectroscopy signals |
| topic | near-infrared spectroscopy neonates respiratory rate cerebral oxygenation signal quality assessment |
| url | https://www.mdpi.com/1424-8220/23/9/4487 |
| work_keys_str_mv | AT naserhakimi respiratoryrateextractionfromneonatalnearinfraredspectroscopysignals AT mohammadshahbakhti respiratoryrateextractionfromneonatalnearinfraredspectroscopysignals AT jornmhorschig respiratoryrateextractionfromneonatalnearinfraredspectroscopysignals AT thomasalderliesten respiratoryrateextractionfromneonatalnearinfraredspectroscopysignals AT frankvanbel respiratoryrateextractionfromneonatalnearinfraredspectroscopysignals AT willynjmcolier respiratoryrateextractionfromneonatalnearinfraredspectroscopysignals AT jeroendudink respiratoryrateextractionfromneonatalnearinfraredspectroscopysignals |