Detection of neonatal asphyxia by analyzing the complexity of electroencephalography data DOI Creative Commons
Sou Nobukawa,

Kurnianingsih,

Isshu Wakita

et al.

Frontiers in Applied Mathematics and Statistics, Journal Year: 2025, Volume and Issue: 11

Published: March 19, 2025

Introduction In neonates, the early detection of asphyxia improves survival rates and prevents long-term complications. neonatal care, physiological signals, including heart rate oxygen saturation, are routinely monitored. However, neonates with neurological conditions such as hypoxic-ischemic encephalopathy (HIE) require direct neural monitoring. Electroencephalography (EEG) is a non-invasive method for assessing activity therefore can effectively detect signs asphyxia. Although studies on HIE have utilized clinical-grade EEG systems, real-world application wearable devices in broader care remains underexplored. this study, we aimed to investigate effectiveness detecting without restricting its progression (HIE). Methods We used Fuzzy Entropy (FuzzyEn) perform power spectral complexity analyses signal data healthy those Results found that both delta band decrease asphyxia, which consistent HIE. Furthermore, FuzzyEn combination absolute measurements captured complementary information led improved accuracy enhanced identification performance. Discussion Wearable scalable accessible use resource-constrained environments (such rural developing regions) be integrated into Internet Things (IoT) systems. Our findings highlight potential may contribute more effective outcomes.

Language: Английский

Detection of neonatal asphyxia by analyzing the complexity of electroencephalography data DOI Creative Commons
Sou Nobukawa,

Kurnianingsih,

Isshu Wakita

et al.

Frontiers in Applied Mathematics and Statistics, Journal Year: 2025, Volume and Issue: 11

Published: March 19, 2025

Introduction In neonates, the early detection of asphyxia improves survival rates and prevents long-term complications. neonatal care, physiological signals, including heart rate oxygen saturation, are routinely monitored. However, neonates with neurological conditions such as hypoxic-ischemic encephalopathy (HIE) require direct neural monitoring. Electroencephalography (EEG) is a non-invasive method for assessing activity therefore can effectively detect signs asphyxia. Although studies on HIE have utilized clinical-grade EEG systems, real-world application wearable devices in broader care remains underexplored. this study, we aimed to investigate effectiveness detecting without restricting its progression (HIE). Methods We used Fuzzy Entropy (FuzzyEn) perform power spectral complexity analyses signal data healthy those Results found that both delta band decrease asphyxia, which consistent HIE. Furthermore, FuzzyEn combination absolute measurements captured complementary information led improved accuracy enhanced identification performance. Discussion Wearable scalable accessible use resource-constrained environments (such rural developing regions) be integrated into Internet Things (IoT) systems. Our findings highlight potential may contribute more effective outcomes.

Language: Английский

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