High-Frequency Oscillations in the Scalp EEG of Intensive Care Unit Patients With Altered Level of Consciousness

2020 ◽  
Vol 37 (3) ◽  
pp. 246-252
Author(s):  
Taissa Ferrari-Marinho ◽  
Piero Perucca ◽  
Mina Amiri ◽  
Francois Dubeau ◽  
Jean Gotman ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
High Frequency ◽  
Altered Level ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Level Of Consciousness

scholarly journals A Neuromorphic Spiking Neural Network Detects Epileptic High Frequency Oscillations in the Scalp EEG

2021 ◽  
Author(s):  
Karla Burelo ◽  
Georgia Ramantani ◽  
Giacomo Indiveri ◽  
Johannes Sarnthein
Keyword(s):  
Low Power ◽  
Seizure Frequency ◽  
High Frequency ◽  
Therapy Monitoring ◽  
Non Invasive ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Eeg Recordings ◽  
Active Epilepsy ◽  
Wearable Electronic Devices

Abstract Background: Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The demand for therapy monitoring in epilepsy has kindled interest in compact wearable electronic devices for long- term EEG recording. Spiking neural networks (SNN) have been shown to be optimal architectures for being embedded in compact low-power signal processing hardware. Methods: We analyzed 20 scalp EEG recordings from 11 patients with pediatric focal lesional epilepsy. We designed a custom SNN to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band. Results: We identified the optimal SNN parameters to automatically detect EoI and reject artifacts. The occurrence of HFO thus detected was associated with active epilepsy with 80% accuracy. The HFO rate mirrored the decrease in seizure frequency in 8 patients (p = 0.0047). Overall, the HFO rate correlated with seizure frequency (rho = 0.83, p < 0.0001, Spearman’s correlation).Conclusions: The fully automated SNN detected clinically relevant HFO in the scalp EEG. This is a further step towards non-invasive epilepsy monitoring with a low-power wearable device.

scholarly journals High-frequency oscillations in scalp EEG mirror seizure frequency in pediatric focal epilepsy

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ece Boran ◽  
Johannes Sarnthein ◽  
Niklaus Krayenbühl ◽  
Georgia Ramantani ◽  
Tommaso Fedele
Keyword(s):  
Seizure Frequency ◽  
Epilepsy Surgery ◽  
High Frequency ◽  
Focal Epilepsy ◽  
Low Noise ◽  
Drug Resistant ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Custom Made ◽  
Active Epilepsy

Abstract High-frequency oscillations (HFO) are promising EEG biomarkers of epileptogenicity. While the evidence supporting their significance derives mainly from invasive recordings, recent studies have extended these observations to HFO recorded in the widely accessible scalp EEG. Here, we investigated whether scalp HFO in drug-resistant focal epilepsy correspond to epilepsy severity and how they are affected by surgical therapy. In eleven children with drug-resistant focal epilepsy that underwent epilepsy surgery, we prospectively recorded pre- and postsurgical scalp EEG with a custom-made low-noise amplifier (LNA). In four of these children, we also recorded intraoperative electrocorticography (ECoG). To detect clinically relevant HFO, we applied a previously validated automated detector. Scalp HFO rates showed a significant positive correlation with seizure frequency (R2 = 0.80, p < 0.001). Overall, scalp HFO rates were higher in patients with active epilepsy (19 recordings, p = 0.0066, PPV = 86%, NPV = 80%, accuracy = 84% CI [62% 94%]) and decreased following successful epilepsy surgery. The location of the highest HFO rates in scalp EEG matched the location of the highest HFO rates in ECoG. This study is the first step towards using non-invasively recorded scalp HFO to monitor disease severity in patients affected by epilepsy.

scholarly journals High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Peter Höller ◽  
Eugen Trinka ◽  
Yvonne Höller
Keyword(s):  
High Frequency ◽  
Visual Detection ◽  
Signal To Noise Ratio ◽  
Physiological Activity ◽  
Automated Detection ◽  
Detection Algorithms ◽  
Scalp Eeg ◽  
High Frequency Oscillations ◽  
Scalp Electroencephalogram ◽  
Electroencephalogram Eeg

High-frequency oscillations (HFOs) in the electroencephalogram (EEG) are thought to be a promising marker for epileptogenicity. A number of automated detection algorithms have been developed for reliable analysis of invasively recorded HFOs. However, invasive recordings are not widely applicable since they bear risks and costs, and the harm of the surgical intervention of implantation needs to be weighted against the informational benefits of the invasive examination. In contrast, scalp EEG is widely available at low costs and does not bear any risks. However, the detection of HFOs on the scalp represents a challenge that was taken on so far mostly via visual detection. Visual detection of HFOs is, in turn, highly time-consuming and subjective. In this review, we discuss that automated detection algorithms for detection of HFOs on the scalp are highly warranted because the available algorithms were all developed for invasively recorded EEG and do not perform satisfactorily in scalp EEG because of the low signal-to-noise ratio and numerous artefacts as well as physiological activity that obscures the tiny phenomena in the high-frequency range.

Admission to a Pediatric Intensive Care Unit for Bacterial Meningitis: Review of 168 Cases

1995 ◽  
Vol 10 (5) ◽  
pp. 253-260 ◽  
Author(s):  
Marisa Tucci ◽  
Marc H. Lebel ◽  
Marie Gauthier ◽  
Catherine A. Farrell ◽  
Jacques Lacroix
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Bacterial Meningitis ◽  
Pediatric Intensive Care Unit ◽  
Hormone Secretion ◽  
Pediatric Intensive Care ◽  
Hemodynamic Instability ◽  
Haemophilus Influenzae Type ◽  
Altered Level ◽  
Neurological Sequelae

We performed a retrospective analysis of the charts of 168 patients (1 week to 17 years of age) admitted to a pediatric intensive care unit (PICU) with bacterial meningitis over an 11-year period (1980–1990) to delineate clinical characteristics and outcome. The four major reasons for PICU admission were an altered level of consciousness (70%), hemodynamic instability (33%), seizures (13%), and apnea (7%). Many children had more than one reason for admission to the PICU. The pathogens identified included Haemophilus influenzae type b in 71 (42%) patients, Neisseria meningitidis in 33 (20%), Streptococcus pneumoniae (SP) in 23 (14%), Group B Streptococcus (GBS) in 18 (11%), Escherichia coli in 7 (4%), and others in 7 (4%). Overall mortality was 13% (22 of 168); most deaths (12/22) occurred within 24 hours of admission. The highest mortality rate was associated with GBS meningitis (39%). Average duration of stay in the PICU was 2.9 days. Complications in the PICU included seizures (32%), hemodynamic instability (23%), hyponatremia (21%), syndrome of inappropriate antidiuretic hormone secretion (13%), disseminated intravascular coagulation (12%), and hypernatremia (6%). Ninety-five percent (138/146) of the survivors were evaluated between 1 month and 1 year after discharge: 79% had no significant neurological sequelae, 14% had mild sequelae, and 7% remained with major neurological sequelae. Moderate or severe hearing deficits were detected in 13% of those evaluated (13 of 102). Patients with SP and GBS meningitis had the highest incidence of complications, sequelae, and mortality. The majority of deaths due to bacterial meningitis, in a PICU, occur early, seem unavoidable, and result from neurological or hemodynamic dysfunction. The fact that the majority of survivors have a normal outcome despite a complicated course favors provision of close surveillance and aggressive management in a PICU setting.

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