Detection of convulsive seizures using surface electromyography

Beniczky, Sándor; Conradsen, Isa; Wolf, Peter

doi:10.1111/epi.14048

Cited by 33 publications

(33 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These devices and their effectiveness are discussed in detail in other articles from this supplement. 12,51,52 Some evidence suggests that nocturnal supervision reduces the risk of SUDEP, 42,53 indirectly supporting the view that timely postictal intervention by a caregiver could counteract some of the mechanisms at stake in SUDEP, such as the prone position. Other indirect arguments pointing to the same conclusion have been derived from epilepsy monitoring unit (EMU) data.…”

Section: Warning Of An Ongoing Seizurementioning

confidence: 97%

See 1 more Smart Citation

Wearable devices for sudden unexpected death in epilepsy prevention

et al. 2018

View full text Add to dashboard Cite

Sudden unexpected death in epilepsy (SUDEP) is most often associated with the occurrence of generalized tonic-clonic seizures (GTCS), a seizure type that can now be detected with high sensitivity and specificity by wearable or bed devices. The recent development in such devices and their performance offer multiple opportunities to tackle SUDEP and its prevention. Reliable GTCS detection might help physicians optimize antiepileptic treatment, which could in turn reduce the risk of SUDEP. GTCS-triggered alarms can lead to immediate intervention by caregivers that are also likely to decrease the odd of SUDEP. The biosignals used to detect GTCS might provide novel SUDEP biomarkers, in particular, by informing on several important characteristics of the ictal and postictal periods (type of GTCS, duration of tonic phase, rotation in the prone position, presence and duration of postictal immobility and bradycardia, rise in electrodermal activity). Other biosensors not yet used for detecting GTCS might provide complementary information, such as the presence and intensity of ictal/postictal hypoxemia. The above biomarkers, if strongly predictive, could help identify patients at very high risk of SUDEP, enabling better assessment of individual risk, as well as selection of appropriate patients for clinical studies aiming at preventing SUDEP. The same biosignals could also be used as ancillary biomarkers to test the impact of various interventions before moving to highly challenging randomized controlled trials with SUDEP as a primary outcome.

show abstract

Section: Warning Of An Ongoing Seizurementioning

confidence: 97%

“…Several commercially available wearable devices are providing reliable detection of GTCS with an associated alarm that can prompt immediate intervention from surrounding relatives or caregivers. These devices and their effectiveness are discussed in detail in other articles from this supplement …”

Section: Warning Of An Ongoing Seizurementioning

confidence: 99%

Wearable devices for sudden unexpected death in epilepsy prevention

et al. 2018

View full text Add to dashboard Cite

show abstract

“…I would like to thank the members of the Dutch Tele‐Epilepsy Consortium for the work on which this paper is based.…”

Section: Acknowledgmentmentioning

confidence: 99%

Movement‐based seizure detection

Arends

2018

Epilepsia

View full text Add to dashboard Cite

This is a critical review and comment on the use of movement detection in epileptic seizures. The detection of rhythmic movement components, such as the clonic part of tonic-clonic seizures, is essential in all seizure detection based on movement sensors. Of the many available movement sensor types, accelerometric sensors are used most often. Eleven video-electroencephalographic (EEG) and 1 field study have been carried out. The results of these clinical trials depend on the population, study design, and seizure evolution. In video-EEG monitoring units, sensitivity for tonic-clonic seizures varied from 31% to 95%, and positive predictive value from 4% to 60%. In a field trial in a residential adult population with intellectual disability, sensitivity was 14% and positive predictive value was 82%, whereas in patients admitted to an epilepsy clinic, a bed sensor had a sensitivity of 84% (no positive predictive value was given). The algorithms using the "rhythmic movement" component at the end of a tonic-clonic seizure are reliable (few false-positive alarms) but miss less typical seizure patterns that are mostly present in people with associated brain development disturbances. Other modalities (heart rate and electromyography) are needed to increase the detection performance. Advanced accelerometric techniques allow us to gain greater insight into seizure evolution patterns, possibilities for neuromodulation, and the influence of antiepileptic drugs on specific seizure components.

show abstract

“…The primary methods used to detect seizures are detailed in reviews focusing on scalp EEG, surface electromyography (EMG), movement‐based detection, and multimodal seizure detection . Scalp EEG offers the unique advantage of capturing most seizure types, with high sensitivity (75%‐90%), but also a high rate of false alarms (0.1 and 5 per hour) .…”

mentioning

confidence: 99%

“…It is not currently adapted to chronic ambulatory recordings, although this might change with the development of subcutaneously implanted electrodes. Surface EMG is typically used for detecting convulsive seizures, with 2 large‐scale blinded prospective studies demonstrating high sensitivity (76%‐100%) with average false‐alarm rate ranging from 0.7 to 2.5/24 h . Movement‐based GTCS detection, primarily using accelerometry sensors, is associated with highly variable sensitivity (31%‐95%) and positive predictive value (4%‐60%) across video‐EEG studies, whereas a field study reported even lower sensitivity (14%) .…”

mentioning

confidence: 99%