Monitoring heart period variability changes during seizures. II. Diversity and trends

Vaughn, Bradley V.; Quint, Stephen R.; Tennison, Michael B.; Messenheimer, John A.

doi:10.1016/0896-6974(95)00061-5

Cited by 17 publications

(35 citation statements)

References 19 publications

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“…Q-T), the RHR slope and R-R variability. 15,16,20 Reversible ictal alterations in EKG morphology (see Fig. 5) while likely less prevalent than tachycardia, may have higher specificity and considerably increase speed of detection (e.g.…”

Section: Discussionmentioning

confidence: 99%

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Automated Seizure Detection Using Ekg

Osorio

2014

Int. J. Neur. Syst.

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Changes in heart rate, most often increases, are associated with the onset of epileptic seizures and may be used in lieu of cortical activity for automated seizure detection. The feasibility of this aim was tested on 241 clinical seizures from 81 subjects admitted to several Epilepsy Centers for invasive monitoring for evaluation for epilepsy surgery. The performance of the EKG-based seizure detection algorithm was compared to that of a validated algorithm applied to electrocorticogram (ECoG). With the most sensitive detection settings [threshold T: 1.15; duration D: 0 s], 5/241 seizures (2%) were undetected (false negatives) and with the highest [T: 1.3; D: 5 s] settings, the number of false negative detections rose to 34 (14%). The rate of potential false positive (PFP) detections was 9.5/h with the lowest and 1.1/h with the highest T, D settings. Visual review of 336 ECoG segments associated with PFPs revealed that 120 (36%) were associated with seizures, 127 (38%) with bursts of epileptiform discharges and only 87 (26%) were true false positives. Electrocardiographic (EKG)-based seizure onset detection preceded clinical onset by 0.8 s with the lowest and followed it by 13.8 s with the highest T, D settings. Automated EKG-based seizure detection is feasible and has potential clinical utility given its ease of acquisition, processing, high signal/noise and ergonomic advantages viz-a-viz EEG (electroencephalogram) or ECoG. Its use as an "electronic" seizure diary will remedy in part, the inaccuracies of those generated by patients/care-givers in a cost-effective manner.

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Section: Discussionmentioning

confidence: 99%

“…[10][11][12][13][14][15][16][17][18][19][20][21][22] Automated seizure detection using heart rate has been previously attempted at a small scale. 23,24 This study demonstrates the feasibility of real-time automated seizure detection based on heart rate changes on a large, good-quality dataset.…”

Section: Introductionmentioning

confidence: 99%

Automated Seizure Detection Using Ekg

Osorio

2014

Int. J. Neur. Syst.

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“…(2004) in 7 of 19 patients (36.8%), of which 16% (3 patients) expressed ictal asystoles, too. In addition, Vaughn et al. (1996) evidenced HR deceleration in 8 of 12 patients (66.7%) with complex partial and generalized seizures.…”

Section: Interictal and Ictal Cardiac Effectsmentioning

confidence: 96%

“…These observations indicate a high incidence of seizures preceded by IT. Indeed, later studies have shown that preictal tachycardia may occur in ∼50% of patients (Vaughn et al., 1996; Zijlmans et al., 2002) and 75% of recorded seizures (Schernthaner et al., 1999; Leutmezer et al., 2003). Most often, preictal tachycardia is associated with seizures of mesial temporal lobe origin (Leutmezer et al., 2003; Di Gennaro et al., 2004), which is again not unexpected considering the high TLE incidence.…”

Section: Interictal and Ictal Cardiac Effectsmentioning

confidence: 99%

“…When such emotional, motor or autonomic effects are followed by ictal cardiac changes, the latter could be regarded as adaptive physiologic responses to the former. However, ITs often occur prior to, or in the absence of, any clinical manifestation of seizures, and the second condition is valid in IB cases, as well (Blumhardt et al., 1986; Vaughn et al., 1996; Leutmezer et al., 2003). In addition, experimental studies on ictal cardiac changes were performed in anesthetized and/or paralyzed animals (Lathers et al., 1987; Mameli et al., 2006).…”

Section: Mechanisms Supporting Cardiovascular Changes In Epilepsymentioning

confidence: 99%

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Autonomic alterations and cardiac changes in epilepsy

2010

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SUMMARYStudies with heart rate variability have revealed interictal autonomic alterations in patients with epilepsy. In addition, epilepsy is frequently associated with ictal tachycardia or bradycardia, which sometimes precedes the onset of seizures. Ictal tachycardia is sometimes associated with electrocardiography (ECG) morphologic changes and ictal bradycardia often progresses to asystole. Such cardiac manifestations of seizures have been hypothesized as possible causes for sudden unexplained death in epilepsy (SUPEP). The present review relates to interictal and ictal cardiac manifestations of epilepsy with focus on heart rate, heart rate variability, and ECG changes.Aspects of the supporting mechanisms are discussed and attention is drawn to the interaction between central and peripheral effects, interictal autonomic conditions, ictal autonomic discharges, and administration of antiepileptic drugs in shaping the ictal cardiac changes. Because these interactions are complex and not totally understood, closer surveillance of patients and more experimental work is necessary to elucidate the mechanistic support of autonomic and cardiac changes in epilepsy, and to design better strategies to avoid their undesirable effects. It is also suggested that some of these changes could be used as predictors or markers for the onset of seizures.

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Seizure detection: do current devices work? And when can they be useful?

Zhao

Lhatoo

2018

Curr Neurol Neurosci Rep

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There are two broad categories of detection devices: EEG-based and non-EEG-based systems. Wireless wearable EEG devices are now available both in research and commercial arenas. Neuro-stimulation devices are currently evolving and initial experiences of these show potential promise. As for non-EEG devices, different detecting systems show different sensitivity according to the different patient and seizure types. Regardless, when used in combination, these modalities may complement each other to increase positive predictive value. Although some devices with high sensitivity are promising, practical widespread use of such detection systems is still some way away. More research and experience are needed to evaluate the most efficient and integrated systems, to allow for better approaches to detection and prediction of seizures. The concept of closed-loop systems and prompt intervention may substantially improve quality of life for patients and carers.

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Monitoring heart period variability changes during seizures. II. Diversity and trends

Cited by 17 publications

References 19 publications

Automated Seizure Detection Using Ekg

Automated Seizure Detection Using Ekg

Autonomic alterations and cardiac changes in epilepsy

Seizure detection: do current devices work? And when can they be useful?

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