Reduced electrode arrays for the automated detection of rhythmic and periodic patterns in the intensive care unit: Frequently tried, frequently failed?

Herta, Johannes; Koren, Johannes; Fürbass, Franz; Hartmann, M.; Gruber, Andreas; Baumgartner, Christoph

doi:10.1016/j.clinph.2017.04.012

Cited by 30 publications

(26 citation statements)

References 22 publications

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“…• Detection algorithms generally perform better on seizures of temporal lobe origin as compared to those of extratemporal origin • In an outpatient setting, use of scalp-EEG-based seizure-detection is limited because patients won't tolerate wearing EEG electrode arrays in everyday life reduction of the number of electrodes is desirable. [24][25][26] Use of only 8 frontal and temporal electrodes yielded an average detection sensitivity of 79%; and use of only 7 temporal, parietal, and occipital electrodes an average detection sensitivity of 68%, as compared to a sensitivity of 84% for all 21 channels of the International 10-20-system. 25 After data acquisition, all algorithms apply some kind of artifact rejection.…”

Section: Key Pointsmentioning

confidence: 97%

“…When using multiple EEG channels, the montage can be of critical importance for performance of the algorithm . Furthermore, both for computational reasons and for patient comfort (especially in outpatient settings), a selection and reduction of the number of electrodes is desirable . Use of only 8 frontal and temporal electrodes yielded an average detection sensitivity of 79%; and use of only 7 temporal, parietal, and occipital electrodes an average detection sensitivity of 68%, as compared to a sensitivity of 84% for all 21 channels of the International 10‐20‐system …”

Section: Algorithms For Scalp‐eeg–based Seizure Detectionmentioning

confidence: 99%

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Seizure detection using scalp‐EEG

Baumgartner

Koren

2018

Epilepsia

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Scalp electroencephalography (EEG)-based seizure-detection algorithms applied in a clinical setting should detect a broad range of different seizures with high sensitivity and selectivity and should be easy to use with identical parameter settings for all patients. Available algorithms provide sensitivities between 75% and 90%. EEG seizure patterns with short duration, low amplitude, circumscribed focal activity, high frequency, and unusual morphology as well as EEG seizure patterns obscured by artifacts are generally difficult to detect. Therefore, detection algorithms generally perform worse on seizures of extratemporal origin as compared to those of temporal lobe origin. Specificity (false-positive alarms) varies between 0.1 and 5 per hour. Low false-positive alarm rates are of critical importance for acceptance of algorithms in a clinical setting. Reasons for false-positive alarms include physiological and pathological interictal EEG activities as well as various artifacts. To achieve a stable, reproducible performance (especially concerning specificity), algorithms need to be tested and validated on a large amount of EEG data comprising a complete temporal assessment of all interictal EEG. Patient-specific algorithms can further improve sensitivity and specificity but need parameter adjustments and training for individual patients. Seizure alarm systems need to provide on-line calculation with short detection delays in the order of few seconds. Scalp-EEG-based seizure detection systems can be helpful in an everyday clinical setting in the epilepsy monitoring unit, but at the current stage cannot replace continuous supervision of patients and complete visual review of the acquired data by specially trained personnel. In an outpatient setting, application of scalp-EEG-based seizure-detection systems is limited because patients won't tolerate wearing widespread EEG electrode arrays for long periods in everyday life. Recently developed subcutaneous EEG electrodes may offer a solution in this respect.

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Section: Key Pointsmentioning

confidence: 97%

Section: Algorithms For Scalp‐eeg–based Seizure Detectionmentioning

confidence: 99%

Seizure detection using scalp‐EEG

Baumgartner

Koren

2018

Epilepsia

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“…Prior studies on the diagnostic accuracy of abbreviated EEG have used rm-EEG arrays that vary both in total number of electrodes and in montage configuration [4][5][6][7][8][9][10][11][12][13][14][15][16][17]. These arrays intrinsically differ in their sensitivity to detect clinically significant patterns, and it is unwarranted to generalize findings across all forms of rm-EEG.…”

Section: Confounding Factors In Prior Researchmentioning

confidence: 99%

Diagnostic Value of Electroencephalography with Ten Electrodes in Critically Ill Patients

et al. 2020

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Background: In critical care settings, electroencephalography (EEG) with reduced number of electrodes (reduced montage EEG, rm-EEG) might be a timely alternative to the conventional full montage EEG (fm-EEG). However, past studies have reported variable accuracies for detecting seizures using rm-EEG. We hypothesized that the past studies did not distinguish between differences in sensitivity from differences in classification of EEG patterns by different readers. The goal of the present study was to revisit the diagnostic value of rm-EEG when confounding issues are accounted for. Methods: We retrospectively collected 212 adult EEGs recorded at Massachusetts General Hospital and reviewed by two epileptologists with access to clinical, trending, and video information. In Phase I of the study, we re-configured the first 4 h of the EEGs in lateral circumferential montage with ten electrodes and asked new readers to interpret the EEGs without access to any other ancillary information. We compared their rating to the reading of hospital clinicians with access to ancillary information. In Phase II, we measured the accuracy of the same raters reading representative samples of the discordant EEGs in full and reduced configurations presented randomly by comparing their performance to majority consensus as the gold standard. Results: Of the 95 EEGs without seizures in the selected fm-EEG, readers of rm-EEG identified 92 cases (97%) as having no seizure activity. Of 117 EEGs with "seizures" identified in the selected fm-EEG, none of the cases was labeled as normal on rm-EEG. Readers of rm-EEG reported pathological activity in 100% of cases, but labeled them as seizures (N = 77), rhythmic or periodic patterns (N = 24), epileptiform spikes (N = 7), or burst suppression (N = 6). When the same raters read representative epochs of the discordant EEG cases (N = 43) in both fm-EEG and rm-EEG configurations, we found high concordance (95%) and intra-rater agreement (93%) between fm-EEG and rm-EEG diagnoses. Conclusions: Reduced EEG with ten electrodes in circumferential configuration preserves key features of the traditional EEG system. Discrepancies between rm-EEG and fm-EEG as reported in some of the past studies can be in part due to methodological factors such as choice of gold standard diagnosis, asymmetric access to ancillary clinical information, and inter-rater variability rather than detection failure of rm-EEG as a result of electrode reduction per se.

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“…Es gibt aber aus nachvollziehbaren Gründen immer wieder Versuche reduzierte Elektrodenmontagen zu etablieren (Zeitersparnis beim Anlegen der Elektroden, einfachere Handhabung, weniger Personalbedarf). Bisher hat sich aber noch keine reduzierte Montage durchgesetzt, da die Sensitivität für verschiedene pathologische EEG Veränderungen teilweise deutlich herabgesetzt wird [41]. Unsere Arbeitsgruppe konnte in einer rezenten Arbeit zeigen, dass ein mathematischer, automatisierter Ansatz in Zukunft je nach Fragestellung zu spezifisch reduzierten Elektrodenmontagen führen könnte [41].…”

Section: Früherkennung Von Ischämienunclassified

Critical Care EEG: Möglichkeiten und Limitationen

2018

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ZusammenfassungUnklare quantitative und qualitative Bewusstseinsstörungen, nicht-konvulsive Anfälle und Status epileptici sowie Sedierungs- und Therapiemanagement sind Indikationen für die Anwendung von kontinuierlichem EEG Monitoring auf der Intensivstation. Durch technologische und wissenschaftliche Fortschritte gewinnt das Neuromonitoring mittels EEG bei intensivpflichtigen Patienten in den letzten Jahren immer mehr an Bedeutung und kommt immer häufiger zur Anwendung. Aufgrund des hohen personellen und technischen Aufwandes, in Zeiten begrenzter Ressourcen, ist ein pragmatisches Vorgehen bei der Indikationsstellung notwendig. Dies gilt v. a. auf neurologischen Intensivstationen, wo metabolische, ischämische, entzündliche, traumatische und strukturelle Hirnschädigungen besonders oft eine differenzialdiagnostische Abklärung mittels EEG verlangen. Im Rahmen dieses Artikels soll die aktuelle Literatur, wie auch wichtige pathologische EEG Muster anhand von Beispielen übersichtlich dargestellt werden.

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Reduced electrode arrays for the automated detection of rhythmic and periodic patterns in the intensive care unit: Frequently tried, frequently failed?

Cited by 30 publications

References 22 publications

Seizure detection using scalp‐EEG

Seizure detection using scalp‐EEG

Diagnostic Value of Electroencephalography with Ten Electrodes in Critically Ill Patients

Critical Care EEG: Möglichkeiten und Limitationen

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