• Publications
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Line length as a robust method to detect high-activity events: Automated burst detection in premature EEG recordings
OBJECTIVE EEG is a valuable tool for evaluation of brain maturation in preterm babies. Preterm EEG constitutes of high voltage burst activities and more suppressed episodes, called interburstExpand
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Objective differentiation of neonatal EEG background grades using detrended fluctuation analysis
A quantitative and objective assessment of background electroencephalograph (EEG) in sick neonates remains an everyday clinical challenge. We studied whether long range temporal correlationsExpand
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  • Open Access
Automated Respiration Detection from Neonatal Video Data
tl;dr
A method to extract the respiration rate from video data included in a polysomnography. Expand
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  • Open Access
Independent component analysis as a preprocessing step for data compression of neonatal EEG
tl;dr
We propose a novel approach for compressive sampling of the neonatal electro-encefalogram (EEG) data, instead of compressing original EEG channels, first performs a data-reduction, and then compresses the obtained sources. Expand
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Automated artifact removal as preprocessing refines neonatal seizure detection
OBJECTIVE The description and evaluation of algorithms using Independent Component Analysis (ICA) for automatic removal of ECG, pulsation and respiration artifacts in neonatal EEG before automatedExpand
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Early development of synchrony in cortical activations in the human
Highlights • We study the early development of cortical activations synchrony index (ASI).• Cortical activations become increasingly synchronized during the last trimester.• InterhemisphericExpand
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  • Open Access
Interhemispheric synchrony in the neonatal EEG revisited: activation synchrony index as a promising classifier
A key feature of normal neonatal EEG at term age is interhemispheric synchrony (IHS), which refers to the temporal co-incidence of bursting across hemispheres during trace alternant EEG activity. TheExpand
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  • Open Access
Multi-sparse signal recovery for compressive sensing
tl;dr
We exploit multi-sparsity constraints in multiple domains to generate a new convex programming model for multi-sparse signals. Expand
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  • Open Access
Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study
Background To improve the objective assessment of continuous video-EEG (cEEG) monitoring of neonatal brain function, the aim was to relate automated derived amplitude and duration parameters of theExpand
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Multi-structural Signal Recovery for Biomedical Compressive Sensing
tl;dr
A new convex programming problem is generated with multiple convex structure-inducing constraints and linear measurement fitting constraint. Expand
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  • Open Access