Detection of generalized tonic-clonic seizures using surface electromyographic monitoring.

OBJECTIVE: A 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). METHODS: One 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. RESULTS: For 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. SIGNIFICANCE: Detection 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.

Electromyography-based seizure detector: Preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings.

OBJECTIVE: Automatic detection of generalized tonic-clonic seizures (GTCS) will facilitate patient monitoring and early intervention to prevent comorbidities, recurrent seizures, or death. Brain Sentinel (San Antonio, Texas, USA) developed a seizure-detection algorithm evaluating surface electromyography (sEMG) signals during GTCS. This study aims to validate the seizure-detection algorithm using inpatient video-electroencephalography (EEG) monitoring. METHODS: sEMG was recorded unilaterally from the biceps/triceps muscles in 33 patients (17white/16 male) with a mean age of 40 (range 14-64) years who were admitted for video-EEG monitoring. Maximum voluntary biceps contraction was measured in each patient to set up the baseline physiologic muscle threshold. The raw EMG signal was recorded using conventional amplifiers, sampling at 1,024 Hz and filtered with a 60 Hz noise detection algorithm before it was processed with three band-pass filters at pass frequencies of 3-40, 130-240, and 300-400 Hz. A seizure-detection algorithm utilizing Hotelling's T-squared power analysis of compound muscle action potentials was used to identify GTCS and correlated with video-EEG recordings. RESULTS: In 1,399 h of continuous recording, there were 196 epileptic seizures (21 GTCS, 96 myoclonic, 28 tonic, 12 absence, and 42 focal seizures with or without loss of awareness) and 4 nonepileptic spells. During retrospective, offline evaluation of sEMG from the biceps alone, the algorithm detected 20 GTCS (95%) in 11 patients, averaging within 20 s of electroclinical onset of generalized tonic activity, as identified by video-EEG monitoring. Only one false-positive detection occurred during the postictal period following a GTCS, but false alarms were not triggered by other seizure types or spells. SIGNIFICANCE: Brain Sentinel's seizure detection algorithm demonstrated excellent sensitivity and specificity for identifying GTCS recorded in an epilepsy monitoring unit. Further studies are needed in larger patient groups, including children, especially in the outpatient setting.

Automated Processing of Single-Channel Surface Electromyography From Generalized Tonic-Clonic Seizures to Inform Semiology.

PURPOSE: Advances in surface electromyography (sEMG) monitoring allow for long-term data collection in a natural environment, giving objective information that may identify risk of sudden unexpected death in epilepsy and guide clinical decision-making. Generalized tonic-clonic seizure semiology, namely motor tonic and clonic phase duration, may be an important factor in determining the level of seizure control and risk of sudden unexpected death in epilepsy. This study demonstrates a quantitative analysis of sEMG collected with a dedicated wearable device. METHODS: During routine monitoring, 23 generalized tonic-clonic seizures from 19 subjects were simultaneously recorded with video-EEG and sEMG. A continuous wavelet-transform was used to determine the frequency components of sEMG recorded during generalized tonic-clonic seizures. An automated process, incorporating a variant of cross-validation, was created to identify ideal frequencies and magnitude ranges for tonic and clonic phases and determine phase durations. Phase durations determined using sEMG analysis were compared with phase durations determined by independent epileptologists' review of video-EEG. RESULTS: Cross-validation revealed that the optimal frequency bands for tonic and clonic phases are 150 to 270 Hz and 12 to 70 Hz, respectively. The average difference in phase duration calculated using the two methods for tonic and clonic phases and total seizure duration were -0.42 ± 4.94, -5.12 ± 9.68, and -5.11 ± 11.33 seconds, respectively (results presented are TsEMG - TvEEG, µ ± σ). CONCLUSIONS: The automated processing of sEMG presented here accurately identified durations of tonic, clonic, and total motor durations of generalized tonic-clonic seizures similar to durations identified by epileptologists' review of video-EEG.

Absence status induced by lacosamide adjunctive therapy.

Since lacosamide was approved as an adjuvant agent for the treatment of medically refractory focal epilepsy over ten years ago, it is becoming more widely used for the treatment of idiopathic (genetic) generalized epilepsies. Several studies have demonstrated efficacy in reducing primary generalized tonic-clonic seizures (GTCS), but efficacy is less well-characterized for myoclonic and absence seizures. A 29-year-old man with juvenile myoclonic epilepsy and medically refractory GTCS on a combination of levetiracetam and topiramate was started on lacosamide adjunctive therapy with the plan to replace topiramate. While his GTCS became controlled, he was witnessed to have confusional episodes, with waxing and waning responsiveness, lasting a few days, several times a month. After eight months of adjunctive lacosamide therapy, he was admitted to the epilepsy monitoring unit, where paroxysms of generalized spike-and-wave complexes, lasting for 30-90 minutes, were recorded, interrupted only by sleep. During these periods, he demonstrated psychomotor slowing and disorientation on examination. The absence status was successfully broken by lorazepam, and lacosamide was discontinued. The patient had no further confusional episodes at the most recent follow-up visit, four months after discharge.

Ictal laughter and crying: Should they be classified as automatisms?

Gelastic seizures (GS) describe ictal laughter and are associated with hypothalamic lesions, as well as other cortical areas. Dacrystic seizures (DS), characterized by ictal crying, also have been reported in hypothalamic lesions and focal epilepsy. We describe a young girl with drug resistant focal dyscognitive seizures associated with gelastic and dacrystic features. However, neither laughter nor crying was correlated with a stereotyped electroencephalographic (EEG) pattern or involvement of a particular brain region. Additionally, based on the variety of epileptogenic foci associated with GS and DS in the literature, laughter and crying appear to represent ictal or peri-ictal automatisms.