Video-based discomfort detection for infants
Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is fir...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sun, Yue [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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| Übergeordnetes Werk: |
Enthalten in: Machine vision and applications - Springer Berlin Heidelberg, 1988, 30(2018), 5 vom: 13. Aug., Seite 933-944 |
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| Übergeordnetes Werk: |
volume:30 ; year:2018 ; number:5 ; day:13 ; month:08 ; pages:933-944 |
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| DOI / URN: |
10.1007/s00138-018-0968-1 |
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OLC2074633017 |
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| 520 | |a Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. | ||
| 650 | 4 | |a Infant discomfort | |
| 650 | 4 | |a Face detection | |
| 650 | 4 | |a Discomfort/stress detection | |
| 650 | 4 | |a Facial expression recognition | |
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| 700 | 1 | |a Long, Xi |4 aut | |
| 700 | 1 | |a Pourtaherian, Arash |4 aut | |
| 700 | 1 | |a Zinger, Svitlana |4 aut | |
| 700 | 1 | |a de With, Peter H. N. |4 aut | |
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10.1007/s00138-018-0968-1 doi (DE-627)OLC2074633017 (DE-He213)s00138-018-0968-1-p DE-627 ger DE-627 rakwb eng 004 VZ 11 ssgn Sun, Yue verfasserin aut Video-based discomfort detection for infants 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. Infant discomfort Face detection Discomfort/stress detection Facial expression recognition Shan, Caifeng aut Tan, Tao aut Long, Xi aut Pourtaherian, Arash aut Zinger, Svitlana aut de With, Peter H. N. aut Enthalten in Machine vision and applications Springer Berlin Heidelberg, 1988 30(2018), 5 vom: 13. Aug., Seite 933-944 (DE-627)129248843 (DE-600)59385-0 (DE-576)017944139 0932-8092 nnns volume:30 year:2018 number:5 day:13 month:08 pages:933-944 https://doi.org/10.1007/s00138-018-0968-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 30 2018 5 13 08 933-944 |
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10.1007/s00138-018-0968-1 doi (DE-627)OLC2074633017 (DE-He213)s00138-018-0968-1-p DE-627 ger DE-627 rakwb eng 004 VZ 11 ssgn Sun, Yue verfasserin aut Video-based discomfort detection for infants 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. Infant discomfort Face detection Discomfort/stress detection Facial expression recognition Shan, Caifeng aut Tan, Tao aut Long, Xi aut Pourtaherian, Arash aut Zinger, Svitlana aut de With, Peter H. N. aut Enthalten in Machine vision and applications Springer Berlin Heidelberg, 1988 30(2018), 5 vom: 13. Aug., Seite 933-944 (DE-627)129248843 (DE-600)59385-0 (DE-576)017944139 0932-8092 nnns volume:30 year:2018 number:5 day:13 month:08 pages:933-944 https://doi.org/10.1007/s00138-018-0968-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 30 2018 5 13 08 933-944 |
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10.1007/s00138-018-0968-1 doi (DE-627)OLC2074633017 (DE-He213)s00138-018-0968-1-p DE-627 ger DE-627 rakwb eng 004 VZ 11 ssgn Sun, Yue verfasserin aut Video-based discomfort detection for infants 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. Infant discomfort Face detection Discomfort/stress detection Facial expression recognition Shan, Caifeng aut Tan, Tao aut Long, Xi aut Pourtaherian, Arash aut Zinger, Svitlana aut de With, Peter H. N. aut Enthalten in Machine vision and applications Springer Berlin Heidelberg, 1988 30(2018), 5 vom: 13. Aug., Seite 933-944 (DE-627)129248843 (DE-600)59385-0 (DE-576)017944139 0932-8092 nnns volume:30 year:2018 number:5 day:13 month:08 pages:933-944 https://doi.org/10.1007/s00138-018-0968-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 30 2018 5 13 08 933-944 |
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10.1007/s00138-018-0968-1 doi (DE-627)OLC2074633017 (DE-He213)s00138-018-0968-1-p DE-627 ger DE-627 rakwb eng 004 VZ 11 ssgn Sun, Yue verfasserin aut Video-based discomfort detection for infants 2018 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. Infant discomfort Face detection Discomfort/stress detection Facial expression recognition Shan, Caifeng aut Tan, Tao aut Long, Xi aut Pourtaherian, Arash aut Zinger, Svitlana aut de With, Peter H. N. aut Enthalten in Machine vision and applications Springer Berlin Heidelberg, 1988 30(2018), 5 vom: 13. Aug., Seite 933-944 (DE-627)129248843 (DE-600)59385-0 (DE-576)017944139 0932-8092 nnns volume:30 year:2018 number:5 day:13 month:08 pages:933-944 https://doi.org/10.1007/s00138-018-0968-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_2018 GBV_ILN_4277 AR 30 2018 5 13 08 933-944 |
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Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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Abstract Infants are particularly vulnerable to the effects of pain and discomfort, which can lead to abnormal brain development, yielding long-term adverse neurodevelopmental outcomes. In this study, we propose a video-based method for automated detection of their discomfort. The infant face is first detected and normalized. A two-phase classification workflow is then employed, where Phase 1 is subject-independent, and Phase 2 is subject-dependent. Phase 1 derives geometric and appearance features, while Phase 2 incorporates facial landmark-based template matching. An SVM classifier is finally applied to video frames to recognize facial expressions of comfort or discomfort. The method is evaluated using videos from 22 infants. Experimental results show an AUC of 0.87 for the subject-independent phase and 0.97 for the subject-dependent phase, which is promising for clinical use. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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Video-based discomfort detection for infants |
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https://doi.org/10.1007/s00138-018-0968-1 |
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false |
| author2 |
Shan, Caifeng Tan, Tao Long, Xi Pourtaherian, Arash Zinger, Svitlana de With, Peter H. N. |
| author2Str |
Shan, Caifeng Tan, Tao Long, Xi Pourtaherian, Arash Zinger, Svitlana de With, Peter H. N. |
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129248843 |
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| doi_str |
10.1007/s00138-018-0968-1 |
| up_date |
2024-07-03T22:54:56.754Z |
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1803600314246365184 |
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