Detection of Paroxysms in Long-Term, Single-Channel EEG-Monitoring of Patients with Typical Absence Seizures

Kjær, Troels W.; Sørensen, Helge Bjarup Dissing; Groenborg, Sabine; Pedersen, Christina Gundgaard; Duun‐Henriksen, Jonas

doi:10.1109/jtehm.2017.2649491

Cited by 34 publications

(58 citation statements)

References 27 publications

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“…[1][2][3] Many factors contribute to this problem, with unrecognized and undocumented seizures being the most important. 8,9 Recently, many new EEG devices have appeared, combining various electrode configurations and data processing methods, [10][11][12][13][14][15] but none of these have been tested in real-life. These clinical problems also concern the patients, 6 and in the context of epilepsy research the problem of wrongful reporting is also well known.…”

Section: Introductionmentioning

confidence: 99%

“…An EEG acquisition system usable during everyday life could be the tool currently lacking in the toolbox of epilepsy diagnostics and management. 8,9 Recently, many new EEG devices have appeared, combining various electrode configurations and data processing methods, [10][11][12][13][14][15] but none of these have been tested in real-life. In this study, we present the first real-life data on a subcutaneous EEG device for continuous home monitoring of epilepsy.…”

Section: Introductionmentioning

confidence: 99%

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Ultra‐long‐term subcutaneous home monitoring of epilepsy—490 days of EEG from nine patients

et al. 2019

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ObjectiveTo explore the feasibility of home monitoring of epilepsy patients with a novel subcutaneous electroencephalography (EEG) device, including clinical implications, safety, and compliance via the first real‐life test.MethodsWe implanted a beta‐version of the 24/7 EEG SubQ (UNEEG Medical A/S, Denmark) subcutaneously in nine participants with temporal lobe epilepsy. Data on seizures, adverse events, compliance in using the device, and use of antiepileptic drugs (AEDs) were collected. EEG was recorded for up to 3 months, and all EEG data were reviewed visually to identify electrographic seizures. These were descriptively compared to seizure counts and AED changes reported in diaries from the same period.ResultsFour hundred ninety days of EEG and 338 electrographic seizures were collected. Eight participants completed at least 9 weeks of home monitoring, while one cancelled participation after 4 weeks due to postimplantation soreness. In total, 13 cases of device‐related adverse events were registered, none of them serious. Recordings obtained from the device covered 73% of the time, on average (range 45%‐91%). Descriptively, electrographic seizure counts were substantially different from diary seizure counts. We uncovered several cases of underreporting and revealed important information on AED response. Electrographic seizure counts revealed circadian distributions of seizures not visible from seizure diaries.SignificanceThe study shows that home monitoring for up to 3 months with a subcutaneous EEG device is feasible and well tolerated. No serious adverse device‐related events were reported. An objective seizure count can be derived, which often differs substantially from self‐reported seizure counts. Larger clinical trials quantifying the benefits of objective seizure counting should be a priority for future research as well as development of algorithms for automated review of data.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ultra‐long‐term subcutaneous home monitoring of epilepsy—490 days of EEG from nine patients

et al. 2019

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“…Second, algorithms to detect seizures automatically need to be developed using only that limited amount of EEG channels. Previously, reduced electrode montages have been shown useful for seizure detection and documentation for several epilepsy types . Our proof‐of‐concept study showed that behind‐the‐ear EEG is useful for focal seizure detection .…”

Section: Introductionmentioning

confidence: 70%

Visual seizure annotation and automated seizure detection using behind‐the‐ear electroencephalographic channels

et al. 2020

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Objective: Seizure diaries kept by patients are unreliable. Automated electroencephalography (EEG)-based seizure detection systems are a useful support tool to objectively detect and register seizures during long-term video-EEG recording. However, this standard full scalp-EEG recording setup is of limited use outside the hospital, and a discreet, wearable device is needed for capturing seizures in the home setting.We are developing a wearable device that records EEG with behind-the-ear electrodes. In this study, we determined whether the recognition of ictal patterns using only behind-the-ear EEG channels is possible. Second, an automated seizure detection algorithm was developed using only those behind-the-ear EEG channels. Methods: Fifty-four patients with a total of 182 seizures, mostly temporal lobe epilepsy (TLE), and 5284 hours of data, were recorded with a standard video-EEG at University Hospital Leuven. In addition, extra behind-the-ear EEG channels were recorded. First, a neurologist was asked to annotate behind-the-ear EEG segments containing selected seizure and nonseizure fragments. Second, a data-driven algorithm was developed using only behind-the-ear EEG. This algorithm was trained using data from other patients (patient-independent model) or from the same patient (patient-specific model). Results:The visual recognition study resulted in 65.7% sensitivity and 94.4% specificity. By using those seizure annotations, the automated algorithm obtained 64.1% sensitivity and 2.8 false-positive detections (FPs)/24 hours with the patientindependent model. The patient-specific model achieved 69.1% sensitivity and 0.49 FPs/24 hours. Significance: Visual recognition of ictal EEG patterns using only behind-the-ear EEG is possible in a significant number of patients with TLE. A patient-specific seizure detection algorithm using only behind-the-ear EEG was able to detect more seizures automatically than what patients typically report, with 0.49 FPs/24 hours.

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“…The performance of six commercial devices exceeded that of daytime (F 1 -score = 0.81) and nighttime (F 1 -score = 0.25) patient reports [10,[14][15][16][17][18][19]. ePatch (ECG) was the highest performing commercial SDD (F 1score = 1.00) [16], SPEAC (sEMG, midline bicep) was the highest performing GTC detection device (F 1 -score = 0.95) [10], and Actiwave (wireless EEG) was the highest performing absence SDD (F 1 -score = 0.92) [15].…”

Section: Commercial Sdd Performancementioning

confidence: 85%

“…The majority of the studies included in Table 1, which shows the performance data from the validation studies of commercial devices, were conducted in an Epilepsy Monitoring Unit (EMU)-setting. One study was conducted in an outpatient setting [15].…”

Section: Commercial Sdd Performancementioning

confidence: 99%

Seizure detection devices for use in antiseizure medication clinical trials: A systematic review

Kurada

Srinivasan

Hammond

et al. 2019

Seizure

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This study characterizes the current capabilities of seizure detection device (SDD) technology and evaluates the fitness of these devices for use in anti-seizure medication (ASM) clinical trials. Methods: Through a systematic literature review, 36 wireless SDDs featured in published device validation studies were identified. Each device's seizure detection capabilities that addressed ASM clinical trial primary endpoint measurement needs were cataloged. Results: The two most common types of seizures targeted by ASMs in clinical trials are generalized tonic-clonic (GTC) seizures and focal with impaired awareness (FIA) seizures. The Brain Sentinel SPEAC achieved the highest performance for the detection of GTC seizures (F 1-score = 0.95). A non-commercial wireless EEG device achieved the highest performance for the detection of FIA seizures (F 1-score = 0.88). Discussion: A preliminary assessment of device capabilities for measuring selected ASM clinical trial secondary endpoints was performed. The need to address key limitations in validation studies is highlighted in order to support future assessments of SDD fitness for ASM clinical trial use. In tandem, a stepwise framework to streamline device testing is put forth. These suggestions provide a starting point for establishing SDD reporting requirements before device integration into ASM clinical trials. We conducted a systematic literature review, following PRISMA

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Detection of Paroxysms in Long-Term, Single-Channel EEG-Monitoring of Patients with Typical Absence Seizures

Cited by 34 publications

References 27 publications

Ultra‐long‐term subcutaneous home monitoring of epilepsy—490 days of EEG from nine patients

Ultra‐long‐term subcutaneous home monitoring of epilepsy—490 days of EEG from nine patients

Visual seizure annotation and automated seizure detection using behind‐the‐ear electroencephalographic channels

Seizure detection devices for use in antiseizure medication clinical trials: A systematic review

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