Epileptic Seizure Detection and Experimental Treatment: A Review
One-fourths of the patients have medication-resistant seizures and require seizure detection and treatment continuously to cope with sudden seizures. Seizures can be detected by monitoring the brain and muscle activities, heart rate, oxygen level, artificial sounds, or visual signatures through EEG,...
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2020-07-01
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doaj-90b3fba6b21e477691de58318ed505252020-11-25T03:06:47ZengFrontiers Media S.A.Frontiers in Neurology1664-22952020-07-011110.3389/fneur.2020.00701534017Epileptic Seizure Detection and Experimental Treatment: A ReviewTaeho Kim0Phuc Nguyen1Phuc Nguyen2Nhat Pham3Nhat Pham4Nam Bui5Hoang Truong6Sangtae Ha7Tam Vu8Tam Vu9Department of Computer Science, University of Colorado, Boulder, CO, United StatesDepartment of Computer Science, University of Colorado, Boulder, CO, United StatesDepartment of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, United StatesDepartment of Computer Science, University of Colorado, Boulder, CO, United StatesDepartment of Computer Science, University of Oxford, Oxford, United KingdomDepartment of Computer Science, University of Colorado, Boulder, CO, United StatesDepartment of Computer Science, University of Colorado, Boulder, CO, United StatesDepartment of Computer Science, University of Colorado, Boulder, CO, United StatesDepartment of Computer Science, University of Colorado, Boulder, CO, United StatesDepartment of Computer Science, University of Oxford, Oxford, United KingdomOne-fourths of the patients have medication-resistant seizures and require seizure detection and treatment continuously to cope with sudden seizures. Seizures can be detected by monitoring the brain and muscle activities, heart rate, oxygen level, artificial sounds, or visual signatures through EEG, EMG, ECG, motion, or audio/video recording on the human head and body. In this article, we first discuss recent advances in seizure sensing, signal processing, time- or frequency-domain analysis, and classification algorithms to detect and classify seizure stages. Then, we show a strong potential of applying recent advancements in non-invasive brain stimulation technology to treat seizures. In particular, we explain the fundamentals of brain stimulation approaches, including (1) transcranial magnetic stimulation (TMS), (2) transcranial direct current stimulation (tDCS), (3) transcranial focused ultrasound stimulation (tFUS), and how to use them to treat seizures. Through this review, we intend to provide a broad view of both recent seizure diagnoses and treatments. Such knowledge would help fresh and experienced researchers to capture the advancements in sensing, detection, classification, and treatment seizures. Last but not least, we provide potential research directions that would attract seizure researchers/engineers in the field.https://www.frontiersin.org/article/10.3389/fneur.2020.00701/fullseizure detectionbiosignal processingbiosignal classificationbrain stimulationEEG |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Taeho Kim Phuc Nguyen Phuc Nguyen Nhat Pham Nhat Pham Nam Bui Hoang Truong Sangtae Ha Tam Vu Tam Vu |
spellingShingle |
Taeho Kim Phuc Nguyen Phuc Nguyen Nhat Pham Nhat Pham Nam Bui Hoang Truong Sangtae Ha Tam Vu Tam Vu Epileptic Seizure Detection and Experimental Treatment: A Review Frontiers in Neurology seizure detection biosignal processing biosignal classification brain stimulation EEG |
author_facet |
Taeho Kim Phuc Nguyen Phuc Nguyen Nhat Pham Nhat Pham Nam Bui Hoang Truong Sangtae Ha Tam Vu Tam Vu |
author_sort |
Taeho Kim |
title |
Epileptic Seizure Detection and Experimental Treatment: A Review |
title_short |
Epileptic Seizure Detection and Experimental Treatment: A Review |
title_full |
Epileptic Seizure Detection and Experimental Treatment: A Review |
title_fullStr |
Epileptic Seizure Detection and Experimental Treatment: A Review |
title_full_unstemmed |
Epileptic Seizure Detection and Experimental Treatment: A Review |
title_sort |
epileptic seizure detection and experimental treatment: a review |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neurology |
issn |
1664-2295 |
publishDate |
2020-07-01 |
description |
One-fourths of the patients have medication-resistant seizures and require seizure detection and treatment continuously to cope with sudden seizures. Seizures can be detected by monitoring the brain and muscle activities, heart rate, oxygen level, artificial sounds, or visual signatures through EEG, EMG, ECG, motion, or audio/video recording on the human head and body. In this article, we first discuss recent advances in seizure sensing, signal processing, time- or frequency-domain analysis, and classification algorithms to detect and classify seizure stages. Then, we show a strong potential of applying recent advancements in non-invasive brain stimulation technology to treat seizures. In particular, we explain the fundamentals of brain stimulation approaches, including (1) transcranial magnetic stimulation (TMS), (2) transcranial direct current stimulation (tDCS), (3) transcranial focused ultrasound stimulation (tFUS), and how to use them to treat seizures. Through this review, we intend to provide a broad view of both recent seizure diagnoses and treatments. Such knowledge would help fresh and experienced researchers to capture the advancements in sensing, detection, classification, and treatment seizures. Last but not least, we provide potential research directions that would attract seizure researchers/engineers in the field. |
topic |
seizure detection biosignal processing biosignal classification brain stimulation EEG |
url |
https://www.frontiersin.org/article/10.3389/fneur.2020.00701/full |
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