Novel techniques for automated seizure registration: Patients' wants and needs

Hoppe, Christian; Feldmann, Mieke; Blachut, Barbara; Surges, Rainer; Elger, Christian E.; Helmstaedter, Christoph

doi:10.1016/j.yebeh.2015.08.006

Cited by 103 publications

(124 citation statements)

References 12 publications

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“…Uncomfortable cables, electrodes, lights, buttons, and sounds should be avoided as this disturbs the patient and family, even more so in the long term. This was confirmed by a recent survey evaluating patients' desires that revealed strong preference for a seizure detection device that has little interference with daily activities [135] Devices may either present with onboard processing and algorithms or may transmit nonprocessed signals. Onboard processing allows for longer battery life during real-time analysis and an alarm to be triggered when an event is outside of the chosen parameters.…”

Section: Future Directionsmentioning

confidence: 69%

Automated seizure detection systems and their effectiveness for each type of seizure

Ulate‐Campos

Coughlin

Gaínza‐Lein

et al. 2016

Seizure

189

166

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Epilepsy affects almost 1% of the population and most of the approximately 20-30% of patients with refractory epilepsy have one or more seizures per month. Seizure detection devices allow an objective assessment of seizure frequency and a treatment tailored to the individual patient. A rapid recognition and treatment of seizures through closed-loop systems could potentially decrease morbidity and mortality in epilepsy. However, no single detection device can detect all seizure types. Therefore, the choice of a seizure detection device should consider the patient-specific seizure semiologies. This review of the literature evaluates seizure detection devices and their effectiveness for different seizure types. Our aim is to summarize current evidence, offer suggestions on how to select the most suitable seizure detection device for each patient and provide guidance to physicians, families and researchers when choosing or designing seizure detection devices. Further, this review will guide future prospective validation studies.

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Section: Future Directionsmentioning

confidence: 69%

Automated seizure detection systems and their effectiveness for each type of seizure

Ulate‐Campos

Coughlin

Gaínza‐Lein

et al. 2016

Seizure

189

166

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show abstract

“…In general, individuals with epilepsy, PD, and stroke were positive towards using wearables, such as body-worn small separate sensor units [64], gloves [65], smart glasses [66], and “intelligent” clothes [67]. Acceptable wearing time was reported to be 7 days for patients with PD [64].…”

Section: Resultsmentioning

confidence: 99%

Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: a mixed-methods systematic review

2018

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ObjectivesWearable technology is increasingly used to monitor neurological disorders. The purpose of this systematic review was to synthesize knowledge from quantitative and qualitative clinical researches using wearable sensors in epilepsy, Parkinson’s disease (PD), and stroke.MethodsA systematic literature search was conducted in PubMed and Scopus spanning from 1995 to January 2017. A synthesis of the main findings, reported adherence to wearables and missing data from quantitative studies, is provided. Clinimetric properties of measures derived from wearables in laboratory, free activities in hospital, and free-living environment were also evaluated. Qualitative thematic synthesis was conducted to explore user experiences and acceptance of wearables.ResultsIn total, 56 studies (50 reporting quantitative and 6 reporting qualitative data) were included for data extraction and synthesis. Among studies reporting quantitative data, 5 were in epilepsy, 21 PD, and 24 studies in stroke. In epilepsy, wearables are used to detect and differentiate seizures in hospital settings. In PD, the focus is on quantification of cardinal motor symptoms and medication-evoked adverse symptoms in both laboratory and free-living environment. In stroke upper extremity activity, walking and physical activity have been studied in laboratory and during free activities. Three analytic themes emerged from thematic synthesis of studies reporting qualitative data: acceptable integration in daily life, lack of confidence in technology, and the need to consider individualization.ConclusionsWearables may provide information of clinical features of interest in epilepsy, PD and stroke, but knowledge regarding the clinical utility for supporting clinical decision making remains to be established.Electronic supplementary materialThe online version of this article (10.1007/s00415-018-8786-y) contains supplementary material, which is available to authorized users.

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“…The detection specificity needs to be higher to meet patient and physician expectations. Surveys of patients with epilepsy (and their caregivers) have shown that they would strongly consider applying and permanently using a device to detect seizures, especially if the device is wearable (removable) and worn either on the wrist or as a patch over an invisible body site 19. As reported by Van de Vel et al.,20 epilepsy patients, caretakers, and physicians prefer a seizure registration device with at least 90% sensitivity and a FAR such that there is, on average, no more than one FA per seizure detected (and one FA per week for those seizure‐ free).…”

Section: Discussionmentioning

confidence: 99%

Detection of generalized tonic–clonic seizures using surface electromyographic monitoring

et al. 2017

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SummaryObjectiveA prospective multicenter phase III trial was undertaken to evaluate the performance and tolerability in the epilepsy monitoring unit (EMU) of an investigational wearable surface electromyographic (sEMG) monitoring system for the detection of generalized tonic–clonic seizures (GTCSs).MethodsOne hundred ninety‐nine patients with a history of GTCSs who were admitted to the EMU in 11 level IV epilepsy centers for clinically indicated video‐electroencephalographic monitoring also received sEMG monitoring with a wearable device that was worn on the arm over the biceps muscle. All recorded sEMG data were processed at a central site using a previously developed detection algorithm. Detected GTCSs were compared to events verified by a majority of three expert reviewers.ResultsFor all subjects, the detection algorithm detected 35 of 46 (76%, 95% confidence interval [CI] = 0.61–0.87) of the GTCSs, with a positive predictive value (PPV) of 0.03 and a mean false alarm rate (FAR) of 2.52 per 24 h. For data recorded while the device was placed over the midline of the biceps muscle, the system detected 29 of 29 GTCSs (100%, 95% CI = 0.88–1.00), with a detection delay averaging 7.70 s, a PPV of 6.2%, and a mean FAR of 1.44 per 24 h. Mild to moderate adverse events were reported in 28% (55 of 199) of subjects and led to study withdrawal in 9% (17 of 199). These adverse events consisted mostly of skin irritation caused by the electrode patch that resolved without treatment. No serious adverse events were reported.SignificanceDetection of GTCSs using an sEMG monitoring device on the biceps is feasible. Proper positioning of this device is important for accuracy, and for some patients, minimizing the number of false positives may be challenging.

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Novel techniques for automated seizure registration: Patients' wants and needs

Cited by 103 publications

References 12 publications

Automated seizure detection systems and their effectiveness for each type of seizure

Automated seizure detection systems and their effectiveness for each type of seizure

Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: a mixed-methods systematic review

Detection of generalized tonic–clonic seizures using surface electromyographic monitoring

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