scholarly journals Time to response and patient visibility during tonic–clonic seizures in the epilepsy monitoring unit

2018 ◽  
Vol 89 ◽  
pp. 84-88 ◽  
Author(s):  
Kristen Malloy ◽  
Damon Cardenas ◽  
August Blackburn ◽  
Luke Whitmire ◽  
Jose E. Cavazos
Keyword(s):  
Clonic Seizures ◽  
Epilepsy Monitoring

scholarly journals Detecting Tonic-Clonic Seizures in Multimodal Biosignal Data From Wearables: Methodology Design and Validation (Preprint)

2021 ◽  
Author(s):  
Sebastian Böttcher ◽  
Elisa Bruno ◽  
Nikolay V Manyakov ◽  
Nino Epitashvili ◽  
Kasper Claes ◽  
...  
Keyword(s):  
Machine Learning ◽  
False Alarm ◽  
Cross Validation ◽  
Electrodermal Activity ◽  
Supervised Machine Learning ◽  
Data Set ◽  
Test Set ◽  
Out Of Sample ◽  
Clonic Seizures ◽  
Epilepsy Monitoring

BACKGROUND Video electroencephalography recordings, routinely used in epilepsy monitoring units, are the gold standard for monitoring epileptic seizures. However, monitoring is also needed in the day-to-day lives of people with epilepsy, where video electroencephalography is not feasible. Wearables could fill this gap by providing patients with an accurate log of their seizures. OBJECTIVE Although there are already systems available that provide promising results for the detection of tonic-clonic seizures (TCSs), research in this area is often limited to detection from 1 biosignal modality or only during the night when the patient is in bed. The aim of this study is to provide evidence that supervised machine learning can detect TCSs from multimodal data in a new data set during daytime and nighttime. METHODS An extensive data set of biosignals from a multimodal watch worn by people with epilepsy was recorded during their stay in the epilepsy monitoring unit at 2 European clinical sites. From a larger data set of 243 enrolled participants, those who had data recorded during TCSs were selected, amounting to 10 participants with 21 TCSs. Accelerometry and electrodermal activity recorded by the wearable device were used for analysis, and seizure manifestation was annotated in detail by clinical experts. Ten accelerometry and 3 electrodermal activity features were calculated for sliding windows of variable size across the data. A gradient tree boosting algorithm was used for seizure detection, and the optimal parameter combination was determined in a leave-one-participant-out cross-validation on a training set of 10 seizures from 8 participants. The model was then evaluated on an out-of-sample test set of 11 seizures from the remaining 2 participants. To assess specificity, we additionally analyzed data from up to 29 participants without TCSs during the model evaluation. RESULTS In the leave-one-participant-out cross-validation, the model optimized for sensitivity could detect all 10 seizures with a false alarm rate of 0.46 per day in 17.3 days of data. In a test set of 11 out-of-sample TCSs, amounting to 8.3 days of data, the model could detect 10 seizures and produced no false positives. Increasing the test set to include data from 28 more participants without additional TCSs resulted in a false alarm rate of 0.19 per day in 78 days of wearable data. CONCLUSIONS We show that a gradient tree boosting machine can robustly detect TCSs from multimodal wearable data in an original data set and that even with very limited training data, supervised machine learning can achieve a high sensitivity and low false-positive rate. This methodology may offer a promising way to approach wearable-based nonconvulsive seizure detection.

scholarly journals Intranasal midazolam during presurgical epilepsy monitoring is well tolerated, delays seizure recurrence, and protects from generalized tonic-clonic seizures

Epilepsia ◽  
2015 ◽  
Vol 56 (9) ◽  
pp. 1408-1414 ◽  
Author(s):  
Lara Kay ◽  
Philipp S. Reif ◽  
Marcus Belke ◽  
Sebastian Bauer ◽  
Detlef Fründ ◽  
...  
Keyword(s):  
Seizure Recurrence ◽  
Clonic Seizures ◽  
Epilepsy Monitoring ◽  
Intranasal Midazolam

P5346The effect of seizure type on ictal and early post-ictal Heart Rate Variability in patients with focal resistant epilepsy

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M T Faria ◽  
S Rodrigues ◽  
D Dias ◽  
R Rego ◽  
H Rocha ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Refractory Epilepsy ◽  
Ethics Committee ◽  
Wilcoxon Test ◽  
Seizure Type ◽  
Seizure Onset ◽  
Unexpected Death ◽  
Clonic Seizures ◽  
Epilepsy Monitoring

Abstract Background Seizures commonly affect the heart rate and its variability. The increased interest in this area of research is related to the possible connection with sudden unexpected death in epilepsy (SUDEP). Generalized tonic-clonic seizures (GTCS) are reported as the most consistent risk factor for SUDEP. However, the general risk of seizures (and their type) on cardiac function still remains uncertain. Purpose To evaluate the influence of seizure type (GTCS vs non-GTCS) on ictal and early post-ictal Heart Rate Variability (HRV) in patients with refractory epilepsy. Methods From January 2015 to July 2018, we prospectively evaluated 121 patients admitted to our institution's Epilepsy Monitoring Unit with focal resistant epilepsy. All patients underwent a 48-hour Holter recording. We included only patients who had both GTCS and non-GTCS during the recording and selected the first seizure of each type to analyze. HRV (AVNN, SDNN, RMSSD, pNN50, and LF/HF) was evaluated by analyzing 5-min-ECG epochs, starting with the seizure onset (ictal and early post-ictal period). The study was approved by our Institution Ethics Committee and all patients gave informed consent. Results Fourteen patients were included (7 Females, 4 patients with Temporal Lobe Epilepsy). The median age was 39 years (min-max, 18–57). Thirty-six percent presented cardiovascular risk factors without known cardiac disease. A significant statistical reduction was found for AVNN (p=0.013), RMSSD (p=0.008), pNN50 (p=0.005) and HF (p=0.003), during GTCS when compared with non-GTCS (Wilcoxon test, p<0.05; two tailed). Conclusion Our study shows a significant reduced vagal tone during GTCS when compared with non-GTCS. Hence, GTCS had a more pronounced impact on HRV changes than other seizure types, which can be associated with higher SUDEP risk after GTCS.

Effect of Levetiracetam on Cognitive Function and Clonic Seizure Frequency in Children with Epilepsy

2019 ◽  
Vol 19 (9) ◽  
pp. 699-703
Author(s):  
Shihao Zhou ◽  
Qiong Zhan ◽  
Xiaomei Wu
Keyword(s):  
Cognitive Function ◽  
Effective Rate ◽  
Clonic Seizure ◽  
Conventional Group ◽  
Significant Difference ◽  
Random Number Table ◽  
Clonic Seizures ◽  
The Difference ◽  
Experimental Group ◽  
Executive Ability

Background: This study aimed to explore the clinical effect of levetiracetam in the treatment of children with epilepsy. Methods: 136 children with epilepsy were selected from January 2017 to December 2017. According to the random number table method, they were divided into the experimental group and the conventional group, with 68 cases in each group. The conventional group was treated with valproate, while the experimental group was treated with levetiracetam. The effective rate, the cognitive function and the frequency of clonic seizures in the two groups were compared. Results: There was no significant difference in the total effective rate between the two groups (P>0.05). There was no significant difference in attention, executive ability, abstract and orientation scores between the two groups before treatment (P>0.05). After treatment, the focus of attention (106.54±6.56), executive ability (105.76±6.77), abstract and directional score (106.65±6.57) were significantly higher than that of the conventional group. The difference in the two groups was statistically significant (P<0.05). After 3 months of treatment, the frequency of myoclonic seizures (9.22±0.95) and the frequency of tonic-clonic seizures (11.68±1.36) were found to be significantly lower than those of the conventional group, and the difference between the two groups was statistically significant (P<0.05). Conclusion: Levetiracetam is effective in the treatment of children with epilepsy. It can effectively improve the cognitive function of the patients, reduce the frequency of myoclonic seizures and tonic-clonic seizures, and has a high promotion value.

Tonic-clonic seizures as first symptom of a disseminated supraglottic laryngeal cancer

2020 ◽  
Vol 13 (3) ◽  
pp. e233584
Author(s):  
Christian Danstrup ◽  
Maria Andersen
Keyword(s):  
Lymph Node ◽  
Laryngeal Cancer ◽  
Primary Tumour ◽  
Duodenal Mucosa ◽  
Cervical Lymph Nodes ◽  
Sagittal Sinus ◽  
Whole Brain Radiation ◽  
Positron Emission ◽  
Node Metastases ◽  
Clonic Seizures

A 60-year-old man was found unconscious at work, without any signs of trauma. At the site, he presented with tonic-clonic seizures, central facial palsy and eye deviation. A CT scan of the cerebrum did not find bleeding or thrombosis, but contrast enhancement at the superior sagittal sinus and pathological cervical lymph nodes. The MRI demonstrated multiple intracerebral metastases, while a supplementary fluoro-deoxy-glucose positron emission tomography scan revealed metastatic lesions above and below the diaphragm, without signs of a primary tumour. An ear, nose and throat examination found a small supraglottic tumour and cervical lymph node metastases. Following a multidisciplinary team discussion, biopsies from the duodenal mucosa and an inguinal lymph node were performed, showing squamous cell carcinoma with its origin in the head and neck. The patient was diagnosed with a T1N2cM1 supraglottic laryngeal cancer, receiving palliative whole brain radiation therapy but died 11 weeks after the debut of symptoms.

The Minnesota Multiphasic Personality Inventory-2-Restructured Form in the epilepsy monitoring unit

2010 ◽  
Vol 17 (2) ◽  
pp. 252-258 ◽  
Author(s):  
Dona E.C. Locke ◽  
Kristin A. Kirlin ◽  
Michael L. Thomas ◽  
David Osborne ◽  
Duane F. Hurst ◽  
...  
Keyword(s):  
Minnesota Multiphasic Personality Inventory ◽  
Personality Inventory ◽  
Epilepsy Monitoring

scholarly journals Cycles of self‐reported seizure likelihood correspond to yield of diagnostic epilepsy monitoring

Epilepsia ◽  
2021 ◽  
Vol 62 (2) ◽  
pp. 416-425
Author(s):  
Philippa J. Karoly ◽  
Dominique Eden ◽  
Ewan S. Nurse ◽  
Mark J. Cook ◽  
Janelle Taylor ◽  
...  
Keyword(s):  
Epilepsy Monitoring

scholarly journals Video-based Detection of Generalized Tonic-clonic Seizures Using Deep Learning

2021 ◽  
pp. 1-1
Author(s):  
Yonghua Yang ◽  
Rani Sarkis ◽  
Rima El Atrache ◽  
Tobias Loddenkemper ◽  
Christian Meisel
Keyword(s):  
Deep Learning ◽  
Clonic Seizures
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