Proceedings ArticleDOI
Detection of generalized tonic-clonic seizures using short length accelerometry signal
Shitanshu Kusmakar,Chandan Karmakar,Bernard Yan,Terence J. O'Brien,Ramanathan Muthuganapathy,Marimuthu Palaniswami +5 more
- Vol. 2017, pp 4566-4569
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TLDR
A system based on single wrist-worn accelerometer sensor capable of detecting seizures with short duration (≥ 10s) and employing machine learning approach such as kernelized support vector data description (SVDD) is proposed.Abstract:
Epileptic seizures are characterized by the excessive and abrupt electrical discharge in the brain. This asynchronous firing of neurons causes unprovoked convulsions which can be a cause of sudden unexpected death in epilepsy (SUDEP). Remote monitoring of epileptic patients can help prevent SUDEP. Systems based on wearable accelerometer sensors have shown to be effective in ambulatory monitoring of epileptic patients. However, these systems have a trade-off between seizure duration and the false alarm rate (FAR). The FAR of the system decreases as we increase the seizure duration. Further, multiple sensors are used in conjugation to improve the overall performance of the detection system. In this study, we propose a system based on single wrist-worn accelerometer sensor capable of detecting seizures with short duration (≥ 10s). Seizure detection was performed by employing machine learning approach such as kernelized support vector data description (SVDD). The proposed approach is validated on data collected from 12 patients, corresponding to approximately 966h of recording under video-telemetry unit. The algorithm resulted in a seizure detection sensitivity of 95.23% with a mean FAR of 0.72=24h.read more
Citations
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Journal ArticleDOI
Artificial intelligence and machine learning in emergency medicine.
TL;DR: An overview of current AI research relevant to emergency medicine is presented and it is likely that AI technologies will likely become increasingly integrated into emergency medicine in the coming years.
Journal ArticleDOI
Automated seizure detection using wearable devices: A clinical practice guideline of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology
Sándor Beniczky,Samuel Wiebe,Jesper Jeppesen,William O. Tatum,Milan Brázdil,Yuping Wang,Susan T. Herman,Philippe Ryvlin +7 more
TL;DR: The clinical practice guideline (CPG) as discussed by the authors provides recommendations for healthcare personnel working with patients with epilepsy, on the use of wearable devices for automated seizure detection in patients in outpatient, ambulatory settings.
Journal ArticleDOI
Non-electroencephalography-based seizure detection.
Sándor Beniczky,Jesper Jeppesen +1 more
TL;DR: D detection of GTCS is reliable and there are several, validated devices on the market, however, detection of other seizure types needs further research.
Journal ArticleDOI
Seizure detection devices for use in antiseizure medication clinical trials: A systematic review.
TL;DR: Suggestions provide a starting point for establishing SDD reporting requirements before device integration into ASM clinical trials and a stepwise framework to streamline device testing are put forth.
Journal ArticleDOI
Automated seizure detection using wearable devices: A clinical practice guideline of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology
Sándor Beniczky,Samuel Wiebe,Jesper Jeppesen,William O. Tatum,Milan Brázdil,Yuping Wang,Susan T. Herman,Philippe Ryvlin +7 more
TL;DR: In this article, a clinical practice guideline (CPG) is provided for healthcare personnel working with patients with epilepsy on the use of wearable devices for automated seizure detection in patients in outpatient, ambulatory settings.
References
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Journal ArticleDOI
Support Vector Data Description
TL;DR: The Support Vector Data Description (SVDD) is presented which obtains a spherically shaped boundary around a dataset and analogous to the Support Vector Classifier it can be made flexible by using other kernel functions.
Journal ArticleDOI
Sudden unexpected death in epilepsy: risk factors and potential pathomechanisms
TL;DR: It is suggested that SUDEP is caused by the fatal coexistence of several predisposing and triggering factors, including seizure-induced hormonal and metabolic changes, Dysregulation in cardiac and respiratory physiology, dysfunction in systemic and cerebral circulation physiology, and seizure- induced hormonal and metabolism changes might all contribute to SUDEP.
Journal ArticleDOI
Convulsive seizure detection using a wrist-worn electrodermal activity and accelerometry biosensor.
Ming-Zher Poh,Tobias Loddenkemper,Claus Reinsberger,Nicholas C. Swenson,Shubhi Goyal,Mangwe Christabel Sabtala,Joseph R. Madsen,Rosalind W. Picard +7 more
TL;DR: This algorithm can potentially provide a convulsive seizure alarm system for caregivers and objective quantification of seizure frequency and was tested on >4,213 h of recordings from 80 patients and detected 15 (94%) of 16 of the GTC seizures from seven patients with 130 false alarms.
Journal ArticleDOI
Views of patients with epilepsy on seizure prediction devices.
Andreas Schulze-Bonhage,Francisco Sales,Kathrin Wagner,Rute Teotónio,Astrid Carius,Annette Schelle,Matthias Ihle +6 more
TL;DR: Patients views on the relevance, performance requirements, and implementation of seizure prediction devices have so far not been evaluated in a standardized form are reported, supporting the view that seizure prediction is of high interest to patients with uncontrolled epilepsy.
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