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

Y. Sun; D. Kommers; W. Wang; R. Joshi; C. Shan; T. Tan; R. M. Aarts; C. van Pul; P. Andriessen; P. H. N. de With

doi:10.1109/EMBC.2019.8857597

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

Y. Sun, D. Kommers, W. Wang, R. Joshi, C. Shan, T. Tan, R. M. Aarts, C. van Pul, P. Andriessen, P. H. N. de With

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer 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-2	Engels
Titel	2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Plaats van productie	Piscataway
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	5995-5999
Aantal pagina's	5
ISBN van elektronische versie	978-1-5386-1311-5
DOI's	https://doi.org/10.1109/EMBC.2019.8857597
Status	Gepubliceerd - jul 2019
Evenement	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019) - City Cube Berlin, Berlin, Duitsland Duur: 23 jul 2019 → 27 jul 2019 https://embc.embs.org/2019/

Congres

Congres	41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)
Verkorte titel	EMBC 2019
Land	Duitsland
Stad	Berlin
Periode	23/07/19 → 27/07/19
Internet adres	https://embc.embs.org/2019/

Trefwoorden

Feature extraction
Pediatrics
Pain
Acceleration
Motion segmentation
Monitoring
Correlation

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10.1109/EMBC.2019.8857597

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Perinatal Medicine
M.B. (Beatrijs) van der Hout-van der Jagt (Content manager) & Eugenie Delvaux (Content manager)
Impact: Research Topic/Theme (at group level)

Citeer dit

Sun, Y., Kommers, D., Wang, W., Joshi, R., Shan, C., Tan, T., Aarts, R. M., Pul, C. V., Andriessen, P., & With, P. H. N. D. (2019). Automatic and continuous discomfort detection for premature infants in a NICU using video-based motion analysis. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019 (blz. 5995-5999). [8857597] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2019.8857597

Sun, Y. ; Kommers, D. ; Wang, W. ; Joshi, R. ; Shan, C. ; Tan, T. ; Aarts, R. M. ; Pul, C. van ; Andriessen, P. ; With, P. H. N. de. / Automatic and continuous discomfort detection for premature infants in a NICU using video-based motion analysis. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2019. blz. 5995-5999

@inproceedings{23cb831ed0aa4fdb88923cf4f1be5966,

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

abstract = "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.",

keywords = "Feature extraction, Pediatrics, Pain, Acceleration, Motion segmentation, Monitoring, Correlation",

author = "Y. Sun and D. Kommers and W. Wang and R. Joshi and C. Shan and T. Tan and Aarts, {R. M.} and Pul, {C. van} and P. Andriessen and With, {P. H. N. de}",

year = "2019",

month = jul,

doi = "10.1109/EMBC.2019.8857597",

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booktitle = "2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)<br/>, EMBC 2019 ; Conference date: 23-07-2019 Through 27-07-2019",

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}

Sun, Y , Kommers, D , Wang, W, Joshi, R, Shan, C, Tan, T, Aarts, RM , Pul, CV , Andriessen, P & With, PHND 2019, Automatic and continuous discomfort detection for premature infants in a NICU using video-based motion analysis. in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019., 8857597, Institute of Electrical and Electronics Engineers, Piscataway, blz. 5995-5999, 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)
, Berlin, Duitsland, 23/07/19. https://doi.org/10.1109/EMBC.2019.8857597

Automatic and continuous discomfort detection for premature infants in a NICU using video-based motion analysis. / Sun, Y.; Kommers, D.; Wang, W.; Joshi, R.; Shan, C.; Tan, T.; Aarts, R. M.; Pul, C. van ; Andriessen, P.; With, P. H. N. de.

2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2019. blz. 5995-5999 8857597.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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T1 - Automatic and continuous discomfort detection for premature infants in a NICU using video-based motion analysis

AU - Sun, Y.

AU - Kommers, D.

AU - Wang, W.

AU - Joshi, R.

AU - Shan, C.

AU - Tan, T.

AU - Aarts, R. M.

AU - Pul, C. van

AU - Andriessen, P.

AU - With, P. H. N. de

PY - 2019/7

Y1 - 2019/7

N2 - 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.

AB - 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.

KW - Feature extraction

KW - Pediatrics

KW - Pain

KW - Acceleration

KW - Motion segmentation

KW - Monitoring

KW - Correlation

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DO - 10.1109/EMBC.2019.8857597

M3 - Conference contribution

C2 - 31947213

SP - 5995

EP - 5999

BT - 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019)<br/>

Y2 - 23 July 2019 through 27 July 2019

ER -

Sun Y , Kommers D , Wang W, Joshi R, Shan C, Tan T et al. Automatic and continuous discomfort detection for premature infants in a NICU using video-based motion analysis. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019. Piscataway: Institute of Electrical and Electronics Engineers. 2019. blz. 5995-5999. 8857597 https://doi.org/10.1109/EMBC.2019.8857597

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

Samenvatting

Congres

Trefwoorden

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Perinatal Medicine

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