Automatic and continuous discomfort detection for premature infants in a NICU using video-based motion analysis

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

6 Citaten (Scopus)

Samenvatting

Frequent pain and discomfort in premature infants can lead to long-term adverse neurodevelopmental outcomes. Video-based monitoring is considered to be a promising contactless method for identification of discomfort moments. In this study, we propose a video-based method for automated detection of infant discomfort. The method is based on analyzing facial and body motion. Therefore, motion trajectories are estimated from frame to frame using optical flow. For each video segment, we further calculate the motion acceleration rate and extract 18 time- and frequency-domain features characterizing motion patterns. A support vector machine (SVM) classifier is then applied to video sequences to recognize infant status of comfort or discomfort. The method is evaluated using 183 video segments for 11 infants from 17 heel prick events. Experimental results show an AUC of 0.94 for discomfort detection and the average accuracy of 0.86 when combining all proposed features, which is promising for clinical use.
Originele taal-2Engels
Titel2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's5995-5999
Aantal pagina's5
ISBN van elektronische versie978-1-5386-1311-5
DOI's
StatusGepubliceerd - jul 2019
Evenement41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)
- City Cube Berlin, Berlin, Duitsland
Duur: 23 jul 201927 jul 2019
https://embc.embs.org/2019/

Congres

Congres41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)
Verkorte titelEMBC 2019
LandDuitsland
StadBerlin
Periode23/07/1927/07/19
Internet adres

Trefwoorden

  • Feature extraction
  • Pediatrics
  • Pain
  • Acceleration
  • Motion segmentation
  • Monitoring
  • Correlation

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