Automatic Separation of Respiratory Flow from Motion in Thermal Videos for Infant Apnea Detection

Ilde Lorato (Corresponding author), Sander Stuijk, Mohammed Meftah, Deedee Kommers, Peter Andriessen, Carola van Pul, Gerard de Haan

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

9 Citaten (Scopus)
53 Downloads (Pure)


Both Respiratory Flow (RF) and Respiratory Motion (RM) are visible in thermal recordings of infants. Monitoring these two signals usually requires landmark detection for the selection of a region of interest. Other approaches combine respiratory signals coming from both RF and RM, obtaining a Mixed Respiratory (MR) signal. The detection and classification of apneas, particularly common in preterm infants with low birth weight, would benefit from monitoring both RF and RM, or MR, signals. Therefore, we propose in this work an automatic RF pixel detector not based on facial/body landmarks. The method is based on the property of RF pixels in thermal videos, which are in areas with a smooth circular gradient. We defined 5 features combined with the use of a bank of Gabor filters that together allow selection of the RF pixels. The algorithm was tested on thermal recordings of 9 infants amounting to a total of 132 minutes acquired in a neonatal ward. On average the percentage of correctly identified RF pixels was 84%. Obstructive Apneas (OAs) were simulated as a proof of concept to prove the advantage in monitoring the RF signal compared to the MR signal. The sensitivity in the simulated OA detection improved for the RF signal reaching 73% against the 23% of the MR signal. Overall, the method yielded promising results, although the positioning and number of cameras used could be further optimized for optimal RF visibility.
Originele taal-2Engels
Aantal pagina's16
Nummer van het tijdschrift18
StatusGepubliceerd - 21 sep. 2021


Funding: This research was performed within the Alarm-Limiting AlgoRithm-based Monitoring (ALARM) project funded by Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) grant number 15345.

Nederlandse Organisatie voor Wetenschappelijk Onderzoek15345


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    • Alarm-Limiting AlgoRithm-based Monitoring

      Stuijk, S. (Project Manager), Sanders, R. (Project communicatie medewerker), van der Hagen, D. (Project communicatie medewerker) & de Mol-Regels, M. (Project communicatie medewerker)


      Project: Onderzoek direct

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