The implementation of an apnea-based perinatal stress calculator
| Autor: | Gunnar Naulaers, Margot Deviaene, Katrien Jansen, Jonathan Moeyersons, Mario Lavanga, Bieke Bollen, O De Wel, S. Van Huffel, Alexander Caicedo, Carolina Varon, Els Ortibus |
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| Přispěvatelé: | Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM) |
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Neonatal intensive care unit Apnea 0206 medical engineering Early life stress 02 engineering and technology Infant Premature Diseases Electroencephalography Logistic regression 03 medical and health sciences 0302 clinical medicine Pregnancy 030225 pediatrics Intensive Care Units Neonatal Stress (linguistics) medicine Heart rate variability Humans ComputingMilieux_MISCELLANEOUS medicine.diagnostic_test business.industry [SCCO.NEUR]Cognitive science/Neuroscience Infant Newborn Infant Pain scale 020601 biomedical engineering Emergency medicine Female medicine.symptom business Infant Premature Stress Psychological |
| Zdroj: | EMBC 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Jul 2019, Berlin, France. pp.6000-6003, ⟨10.1109/EMBC.2019.8856955⟩ |
| ISSN: | 2694-0604 |
| Popis: | Early life stress in the neonatal intensive care unit (NICU) predisposes premature infants to adverse health outcomes. Although those patients experience frequent apneas and sleep-wake disturbances during their hospital stay, clinicians still rely on clinical scales to assess pain and stress burden. This study addresses the relationship between stress and apneic spells in NICU patients to implement an automatic stress detector. EEG, ECG and SpO 2 were recorded from 40 patients for at least 3 hours and the stress burden was assessed using the Leuven Pain Scale. Different logistic regression models were designed to detect the presence or the absence of stress based on the signals reactivity to each apneic spell. The classification shows that stress can be detected with an area under the curve of 0.94 and a misclassification error of 19.23%. These results were obtained via SpO 2 dips and EEG regularity. These findings suggest that stress deepens the physiological reaction to apneas, which could ultimately impact the neurological and behavioral development. |
| Databáze: | OpenAIRE |
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