Article
Behavioral Sciences
Sidsel Armand Larsen, Daniella Terney, Tim Osterkjerhuus, Torsten Vinding Merinder, Kaapo Annala, Andrew Knight, Sandor Beniczky
Summary: In this clinical validation study, an automated audio-video system for real-time detection of major nocturnal motor seizures was developed and validated, showing high sensitivity and suitability for implementation in healthcare institutions.
BRAIN AND BEHAVIOR
(2022)
Article
Biotechnology & Applied Microbiology
Lorenzo Frassineti, Antonio Lanata, Benedetta Olmi, Claudia Manfredi
Summary: The complex dynamics of neonatal seizures pose challenges for detection, while timely diagnosis and treatment are crucial for prognosis and neurodevelopment. Multiscale entropy analysis of heart rate variability shows promise as a valuable pre-screening tool for timely detection of seizure events in newborns.
BIOENGINEERING-BASEL
(2021)
Article
Pediatrics
Rediet Zewdie, Lidet Getachew, Geremew Dubele, Ababo Oluma, Gedion Israel, Kokeb Dese, Gizeaddis Lamesgin Simegn
Summary: A cost-effective and efficient total body cooling and rewarming device was designed and developed to monitor and regulate the neonate core body temperature in the neuroprotective range. The device achieved a high level of accuracy in temperature sensor measurement and has the potential to significantly reduce neonatal brain injury and death due to HIE, especially in low resource settings.
Article
Biochemistry & Molecular Biology
Yong Li, Yanyan Zhang, Andrew Walayat, Yingjie Fu, Bailin Liu, Lubo Zhang, Daliao Xiao
Summary: Nicotine exposure during the perinatal period can induce a sensitive phenotype to neonatal brain hypoxic-ischemic injury in offspring. The H19/miR-181a/ATG5 signaling pathway plays a regulatory role in this process.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Khadijeh Raeisi, Mohammad Khazaei, Pierpaolo Croce, Gabriella Tamburro, Silvia Comani, Filippo Zappasodi
Summary: Our study proposed a novel deep learning model based on Graph Convolutional Neural Networks for automated detection of neonatal seizures, considering both temporal and spatial information of EEG signals. The model showed promising results in leveraging interdependencies among EEG signals and achieving reliable detection of neonatal seizures.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Computer Science, Information Systems
Yasmina Souley Dosso, Daniel Kyrollos, Kimberley J. Greenwood, Joann Harrold, James R. Green
Summary: The development of non-contact patient monitoring applications for the neonatal intensive care unit (NICU) is an active research area, particularly in facial video analysis. This paper evaluates the state-of-the-art in face detection in the NICU setting and demonstrates how fine-tuning can increase neonatal face detector robustness.
Review
Clinical Neurology
Vaidehi Naganur, Shobi Sivathamboo, Zhibin Chen, Shitanshu Kusmakar, Ana Antonic-Baker, Terence J. O'Brien, Patrick Kwan
Summary: This study reviewed the performance of noninvasive wearable devices in detecting epileptic seizures and psychogenic nonepileptic seizures (PNES). The results showed that these devices had high sensitivity but relatively high false alarm rates. Future studies should focus on reducing false alarms, detecting other seizure types and PNES, and conducting longer recordings in the community.
Article
Computer Science, Artificial Intelligence
R. Elakkiya
Summary: Epilepsy is a common chronic neurological disorder, and using EEG signals for processing can improve the accuracy of seizure detection in neonates. The proposed CNN model showed high accuracy in predicting epileptic seizures in neonates, outperforming existing models.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Medicine, General & Internal
Mohammed AlMuqbil, Jawaher Alanazi, Nada Alsaif, Duaa Baarmah, Waleed Altwaijri, Ahmad Alrumayyan, Muhammad Talal Alrifai, Fatmah Othman, Hassan Al-shehri, Saif Alsaif
Summary: This study aimed to determine the clinical characteristics and factors associated with neonatal hypoxic-ischaemic encephalopathy (HIE) and its neurodevelopmental outcomes. Maternal comorbidities and prepartum or intrapartum complications were more common in the HIE group. The severity grade of HIE can be used to predict neurodevelopmental consequences, and enhancing patient care and rehabilitation requires a minimum of 24 months of neurodevelopmental follow-up.
INTERNATIONAL JOURNAL OF GENERAL MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Andrea Tapia-Bustos, Carolyne Lespay-Rebolledo, Valentina Vio, Ronald Perez-Lobos, Emmanuel Casanova-Ortiz, Fernando Ezquer, Mario Herrera-Marschitz, Paola Morales
Summary: Perinatal asphyxia affects oligodendrocytes, neuroinflammation, and cell viability in the telencephalon of rats, with the most significant impact observed at postnatal day 7. Treatment with mesenchymal stem cells (MSCs) can prevent the detrimental effects of perinatal asphyxia on myelination and oligodendrocyte survival.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Clinical Neurology
Joel R. Martin, Paolo G. Gabriel, Jeffrey J. Gold, Richard Haas, Suzanne L. Davis, David D. Gonda, Cynthia Sharpe, Scott B. Wilson, Nicolas C. Nierenberg, Mark L. Scheuer, Sonya G. Wang
Summary: This study used computer vision technology to quantify neonatal movements and trained a binary patting detection algorithm, which successfully reduced false-positive automated seizure detections and improved the accuracy of detecting true seizure activity.
JOURNAL OF CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Obstetrics & Gynecology
Mandira D. Kawakami, Adriana Sanudo, Monica L. P. Teixeira, Solange Andreoni, Josiane Q. X. de Castro, Bernadette Waldvogel, Ruth Guinsburg, Maria Fernanda de Almeida
Summary: The study reveals a significant reduction in neonatal mortality rates associated with perinatal asphyxia in Sao Paulo State, Brazil over the past 10 years, with variables associated with these deaths highlighting the need for public health policies to improve the quality of regionalized perinatal care.
BMC PREGNANCY AND CHILDBIRTH
(2021)
Article
Medicine, General & Internal
Yi Yu, Jinsong Gao, Juntao Liu, Yabing Tang, Mei Zhong, Jing He, Shixiu Liao, Xietong Wang, Xinghui Liu, Yinli Cao, Caixia Liu, Jingxia Sun
Summary: This study identified perinatal maternal characteristics contributing to neonatal asphyxia in term and late-preterm newborns and developed an effective prediction model based on a Chinese birth registry cohort. The model relied on clinical predictors and can identify pregnant women at high risk of asphyxia earlier in pregnancy and childbirth.
FRONTIERS IN MEDICINE
(2022)
Article
Clinical Neurology
Shuang Yu, Rima El Atrache, Jianbin Tang, Michele Jackson, Adam Makarucha, Sarah Cantley, Theodore Sheehan, Solveig Vieluf, Bo Zhang, Jeffrey L. Rogers, Iven Mareels, Stefan Harrer, Tobias Loddenkemper
Summary: This study demonstrates the detection of various seizure types through wearable devices worn on the wrist or ankle, using custom-developed deep-learning models.
Article
Clinical Neurology
Melissa Ann Huberman, Carolina Mallar, Paige M. Kalika
Summary: This study reports a case of a three-week-old female neonate who developed second-degree atrioventricular (AV) heart block and cardiac arrest after initiating lacosamide therapy. The patient was being treated for neonatal seizure with phenobarbital, levetiracetam, and phenytoin. The patient had no known cardiac risk factors before starting lacosamide therapy and experienced no recurring episodes or other cardiac events after medication discontinuation.
PEDIATRIC NEUROLOGY
(2023)
Article
Clinical Neurology
Jaiver Macea, Miguel Bhagubai, Victoria Broux, Maarten De Vos, Wim Van Paesschen
Summary: The performance of an EEG seizure-detector algorithm was evaluated in patients with refractory epilepsy using a wearable device. The sensitivity of the device was found to be 52% in inpatients and 23% in outpatients, with high false alarm rates and low performance scores. Although well-received by patients, the device had side effects and its implementation in clinical practice is currently limited.
Article
Multidisciplinary Sciences
Tim Hermans, Katherine Carkeek, Anneleen Dereymaeker, Katrien Jansen, Gunnar Naulaers, Sabine Van Huffel, Maarten De Vos
Summary: In neonates with hypoxic ischemic encephalopathy, the use of wavelet coherence between EEG power and rSO2 is a promising method for assessing neurovascular coupling. However, fluctuations in SpO2 limit the reliability of previous methods. To address this issue, partial wavelet coherence is proposed to eliminate the influence of SpO2. Furthermore, the study investigates the additional value of novel NVC biomarkers compared to traditional EEG and NIRS biomarkers for identifying brain injury.
SCIENTIFIC REPORTS
(2023)
Letter
Respiratory System
Paul Desbordes, Maarten De Vos, Julie Maes, Frans de Jongh, Karl Sylvester, Claus Franz Vogelmeier, Anh Tuan Dinh-Xuan, Jann Mortensen, Wim Janssens, Marko Topalovic
EUROPEAN RESPIRATORY JOURNAL
(2023)
Article
Engineering, Biomedical
Tim Hermans, Laura Smets, Katrien Lemmens, Anneleen Dereymaeker, Katrien Jansen, Gunnar Naulaers, Filippo Zappasodi, Sabine Van Huffel, Silvia Comani, Maarten De Vos
Summary: This paper proposes a semi-supervised deep learning approach for artefact detection in neonatal EEG. The proposed method outperforms existing state-of-the-art models and achieves good performance on two separate datasets. The results demonstrate the effectiveness of the semi-supervised multi-task training strategy and the relevance of artefact detection for automated EEG analysis.
JOURNAL OF NEURAL ENGINEERING
(2023)
Article
Respiratory System
Kenneth Verstraete, Iwein Gyselinck, Helene Huts, Nilakash Das, Marko Topalovic, Maarten De Vos, Wim Janssens
Summary: This study developed machine learning models to estimate and predict individual treatment effects of interventions in patients with chronic obstructive pulmonary disease (COPD). The results showed that poor lung function and blood eosinophils were the strongest predictors of individual treatment effects. The findings suggest that machine learning models can be used to guide personalized treatment decisions in COPD.
Article
Medicine, General & Internal
Luka Beverin, Marko Topalovic, Armin Halilovic, Paul Desbordes, Wim Janssens, Maarten De Vos
Summary: The study aimed to train a supervised machine learning model that can accurately estimate total lung capacity (TLC) values from spirometry and identify patients who would benefit from complete pulmonary function tests by using the best-performing model. The results demonstrated that the machine learning model can estimate TLC with high accuracy, providing potential for the development of smart home-based spirometry solutions.
FRONTIERS IN MEDICINE
(2023)
Article
Biotechnology & Applied Microbiology
Miguel Bhagubai, Kaat Vandecasteele, Lauren Swinnen, Jaiver Macea, Christos Chatzichristos, Maarten De Vos, Wim Van Paesschen
Summary: This study evaluated a semi-automated multimodal wearable seizure detection framework using bte-EEG and ECG data. The results showed that combining ECG with bte-EEG can improve the accuracy of seizure detection and reduce false alarm rates, while also saving time for both clinicians and patients.
BIOENGINEERING-BASEL
(2023)
Article
Clinical Neurology
Tim Hermans, Mohammad Khazaei, Khadijeh Raeisi, Pierpaolo Croce, Gabriella Tamburro, Anneleen Dereymaeker, Maarten De Vos, Filippo Zappasodi, Silvia Comani
Summary: This study aims to explore the use of microstate (MS) analysis to evaluate global brain dynamics changes during maturation in preterm neonates with normal neurodevelopmental outcome. The study found that MS duration decreased and occurrence increased with age in preterm neonates, and significant changes in MS topographies and transitions occurred when neonates reached 37 weeks. Additionally, the Hurst exponent of the individual MS sequence decreased with age.
Article
Computer Science, Information Systems
Oliver Y. Chen, Florian Lipsmeier, Huy Phan, Frank Dondelinger, Andrew Creagh, Christian Gossens, Michael Lindemann, Maarten de Vos
Summary: Personalized longitudinal disease assessment is crucial for MS diagnosis, management, and therapeutic adaptation. We propose a novel model that utilizes smartphone sensor data to map individual disease trajectories in an automated way, even with missing values. The model incorporates sensor-based assessments and imputation for missing data, and identifies potential markers of MS through a generalized estimation equation. The results demonstrate the potential of this model for personalized MS assessment, suggesting that digitally collected features related to gait, balance, and upper extremity function can serve as useful markers for predicting MS over time.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Neurosciences
Gabrielle Cretot-Richert, Maarten De Vos, Stefan Debener, Martin G. Bleichner, Jeremie Voix
Summary: This study investigates the potential of using EEG recorded inside and around the human ear to determine levels of attention and focus. The results suggest that neural oscillations recorded with ear-EEG can differentiate between levels of cognitive workload and working memory when multi-channel recordings are available.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Respiratory System
Katleen Swinnen, Kenneth Verstraete, Claudia Baratto, Laura Hardy, Maarten De Vos, Marko Topalovic, Guido Claessen, Rozenn Quarck, Catharina Belge, Jean-Luc Vachiery, Wim Janssens, Marion Delcroix
Summary: This study developed and validated a machine learning model to improve the prediction accuracy of PH-LHD in a population of PAH and PH-LHD patients. The model significantly improved the sensitivity of PH-LHD prediction at 100% specificity, and may substantially reduce the number of patients referred for invasive diagnostics without missing PAH diagnoses.
Meeting Abstract
Critical Care Medicine
M. Topalovic, M. De Vos, J. Maes, J. Kaspers, N. Stachowicz, P. Desbordes
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2023)
Meeting Abstract
Transplantation
Amelie Dendooven, Aristotelis Styanidis, Louis Raes, Amaryllis Van Craenenbroeck, Matthias Maeyens, Konstantinos Kotras, Maarten De Vos
NEPHROLOGY DIALYSIS TRANSPLANTATION
(2023)
Article
Respiratory System
Kenneth Verstraete, Nilakash Das, Iwein Gyselinck, Marko Topalovic, Thierry Troosters, James D. Crapo, Edwin K. Silverman, Barry J. Make, Elizabeth A. Regan, Robert Jensen, Maarten De Vos, Wim Janssens
Summary: The shape of MEFVC is associated with CT parameters of emphysema, small airways disease (SAD), and bronchial wall thickening (BWT) in COPD. It is a valuable predictor for emphysema and SAD in moderate-severe COPD, but not a suitable screening tool for early disease phenotypes identified by CT scan.
RESPIRATORY RESEARCH
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Oliver Y. Chen, Vu Duy Thanh, Gilbert Greub, Hengyi Cao, Xingru He, Yannick Muller, Constantinos Petrovas, Haochang Shou, Viet-Dung Nguyen, Bangdong Zhi, Laurent Perez, Jean-Louis Raisaro, Guy Nagels, Maarten de Vos, Wei He, Gottardo Palie Smart, Marcus Munafo, Giuseppe Pantaleo
Summary: This article presents a systematic approach to studying varying brain. It discusses different types of brain variability and provides examples for each. It explores classical analysis of covariance as well as advanced residual analysis methods that aim to decompose the total variance of brain or behavior data. The article also considers innate and acquired brain variability, the neural law of large numbers for big brain data, and the gut-brain axis as an important source of brain variability.
2023 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP, SSP
(2023)
Article
Clinical Neurology
Jaakko Vallinoja, Timo Nurmi, Julia Jaatela, Vincent Wens, Mathieu Bourguignon, Helena Maenpaa, Harri Piitulainen
Summary: The study aimed to assess the effects of lesions related to spastic diplegic cerebral palsy on functional connectivity. Using multiple imaging modalities, the researchers found enhanced functional connectivity in the sensorimotor network of individuals with spastic diplegic cerebral palsy, which was not correlated with hand coordination performance.
CLINICAL NEUROPHYSIOLOGY
(2024)
Article
Clinical Neurology
Francesca Ginatempo, Nicola Loi, John C. Rothwell, Franca Deriu
Summary: This study comprehensively investigated sensorimotor integration in the cranial-cervical muscles of healthy adults and found that the integration of sensory inputs with motor output is profoundly influenced by the type of sensory afferent involved and the functional role played by the target muscle.
CLINICAL NEUROPHYSIOLOGY
(2024)