Line length as a robust method to detect high-activity events: Automated burst detection in premature EEG recordings

Koolen, Ninah; Jansen, Katrien; Vervisch, Jan; Matić, Vladimir; Vos, Maarten De; Naulaers, Gunnar; Huffel, Sabine Van

doi:10.1016/j.clinph.2014.02.015

Cited by 59 publications

(70 citation statements)

References 30 publications

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“…In this paper, we only report the results using the running IBI duration, since this is a very robust measure for EEG activity, and thus cerebral metabolism, as validated by our group in a previous study [31]. In addition, this measure is highly interpretable.…”

Section: Methodsmentioning

confidence: 99%

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Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

et al. 2018

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Graphs can be used to describe a great variety of real-world situations and have therefore been used extensively in different fields. In the present analysis, we use graphs to study the interaction between cerebral function, brain hemodynamics, and systemic variables in premature neonates. We used data from a propofol dose-finding and pharmacodynamics study as a model in order to evaluate the performance of the graph measures to monitor signal interactions. Concomitant measurements of heart rate, mean arterial blood pressure, arterial oxygen saturation, regional cerebral oxygen saturation-measured by means of near-infrared spectroscopy-and electroencephalography were performed in 22 neonates undergoing INSURE (intubation, surfactant administration, and extubation). The graphs used to study the interaction between these signal modalities were constructed using the RBF kernel. Results indicate that propofol induces a decrease in the signal interaction up to 90 minutes after propofol administration, which is consistent with clinical observations published previously. The clinical recovery phase is mainly determined by the EEG dynamics, which were observed to recover much slower compared to the other modalities. In addition, we found a more pronounced loss in cerebral-systemic interactions with increasing propofol dose.

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Section: Methodsmentioning

confidence: 99%

“…The EEG signal is segmented in burst and IBI segments using an in-house algorithm based on the line length [31]. The root mean squared (RMS) value and the duration in time for burst and IBIs in overlapping windows 3 Complexity of two minutes are used as a surrogate for EEG.…”

Section: Methodsmentioning

confidence: 99%

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

et al. 2018

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“…The method was validated using preselected EEG segments and resulted in high agreement compared to three reviewers. A detection method based on the line length feature using the EEG of 10 pre-term infants was presented in Koolen et al (2014). An automatic classification method for burst and suppression events was validated in (Westover et al, 2013) on 20 critical care EEG recordings that were selected based on clinical EEG reports.…”

Section: Introductionmentioning

confidence: 99%

Monitoring burst suppression in critically ill patients: Multi-centric evaluation of a novel method

Fürbass

Herta

Koren

et al. 2016

Clinical Neurophysiology

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Objective To develop a computational method to detect and quantify burst suppression patterns (BSP) in the EEGs of critical care patients. A multi-center validation study was performed to assess the detection performance of the method. Methods The fully automatic method scans the EEG for discontinuous patterns and shows detected BSP and quantitative information on a trending display in real-time. The method is designed to work without setting any patient specific parameters and to be insensitive to EEG artifacts and periodic patterns. For validation a total of 3982 h of EEG from 88 patients were analyzed from three centers. Each EEG was annotated by two reviewers to assess the detection performance and the inter-rater agreement. Results Average inter-rater agreement between pairs of reviewers was κ = 0.69. On average 22% of the review segments included BSP. An average sensitivity of 90% and a specificity of 84% were measured on the consensus annotations of two reviewers. More than 95% of the periodic patterns in the EEGs were correctly suppressed. Conclusion A fully automatic method to detect burst suppression patterns was assessed in a multi-center study. The method showed high sensitivity and specificity. Significance Clinically applicable burst suppression detection method validated in a large multi-center study.

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“…In addition, a long duration of suppression has also identified its relevance with a worsening prognosis in certain cases (e.g., brain injuries caused by asphyxia), and, further, the progression of burst suppression has provided important prognostic information in previously conducted studies [10–12]. Accordingly, researchers have developed methods for quantification of burst suppression through calculations of the occupancy ratio of suppression in burst suppression (BSR) [13], analyses using the duration of suppression (interbursts interval, IBI) [14], and quantitation of a burst suppression probability [15]. …”

Section: Introductionmentioning

confidence: 99%

Novel Burst Suppression Segmentation in the Joint Time-Frequency Domain for EEG in Treatment of Status Epilepticus

Lee

Song

Lee

et al. 2016

Computational and Mathematical Methods in Medicine

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We developed a method to distinguish bursts and suppressions for EEG burst suppression from the treatments of status epilepticus, employing the joint time-frequency domain. We obtained the feature used in the proposed method from the joint use of the time and frequency domains, and we estimated the decision as to whether the measured EEG was a burst segment or suppression segment by the maximum likelihood estimation. We evaluated the performance of the proposed method in terms of its accordance with the visual scores and estimation of the burst suppression ratio. The accuracy was higher than the sole use of the time or frequency domains, as well as conventional methods conducted in the time domain. In addition, probabilistic modeling provided a more simplified optimization than conventional methods. Burst suppression quantification necessitated precise burst suppression segmentation with an easy optimization; therefore, the excellent discrimination and the easy optimization of burst suppression by the proposed method appear to be beneficial.

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Line length as a robust method to detect high-activity events: Automated burst detection in premature EEG recordings

Cited by 59 publications

References 30 publications

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

Monitoring burst suppression in critically ill patients: Multi-centric evaluation of a novel method

Novel Burst Suppression Segmentation in the Joint Time-Frequency Domain for EEG in Treatment of Status Epilepticus

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