Minireview of Epilepsy Detection Techniques Based on Electroencephalogram Signals

Liu, Guangda; Xiao, Ruolan; Xu, Lanyu; Cai, Jing

doi:10.3389/fnsys.2021.685387

Cited by 25 publications

(10 citation statements)

References 62 publications

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“…The major limitation in (Boonyakitanont et al, 2020;Kaur et al, 2021;Liu et al, 2021) is the absence of analysis based on available datasets for epilepsy diagnosis, and discussion on future direction in this field. The reviews conducted in (Liu et al, 2021;Rasheed et al, 2020;Sharmila & Geethanjali, 2019) have narrow research coverage. (Saini & Dutta, 2017;Saminu et al, 2021) have provided an extensive review on the subject topic but lacks coverage based on datasets and hardware developments.…”

Section: Existing Epilepsy Diagnosis Review Papers and Contribution O...mentioning

confidence: 99%

A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets

et al. 2023

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Epilepsy is a common non-communicable, group of neurological disorders affecting more than 50 million individuals worldwide. Different approaches of basic, clinical, and translational research of the human brain have been explored to diagnose, treat, and manage the growing no. of cases of epilepsy. Various hospital information from video, images, signals, forms, and so forth, are retrieved and analysed to develop a consensus for such patients. Electroencephalography (EEG) tests are routinely used to diagnose the type of epilepsy in a clinical setting. Artificial Intelligence algorithms are assisting in the early detection and prediction of epileptic patterns observed in EEG signals. This paper reviews recent and emerging state-of-the-art (SOTA) software and hardware approaches in data selection, signal processing, feature estimation, classification, detection methods, and evaluation metrics applied to open and private EEG datasets from 2014 to 2022. The work summarizes and compares reported works through subjective and objective parameters. Rise in hardware pipeline, start-ups, and companies, deep learning methods in software pipeline and release of free EEG datasets have been observed from 2014 to 2022. SOTA

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Section: Existing Epilepsy Diagnosis Review Papers and Contribution O...mentioning

confidence: 99%

A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets

et al. 2023

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“…Most attempts to predict seizure occurrence utilize information extracted from electroencephalograms 187 . We are not aware of any report of efforts to predict seizure occurrence based on the concentration of any blood component.…”

Section: How Best To Intervenementioning

confidence: 99%

“…Most attempts to predict seizure occurrence utilize information extracted from electroencephalograms. 187 We are not aware of any report of efforts to predict seizure occurrence based on the concentration of any blood component. Consequently, the most appropriate model for doing so would seem to come from the literature about predicting sustained hypoglycemia based on blood glucose levels collected continuously by an in situ sensor.…”

Section: How Best To Intervenementioning

confidence: 99%

Systemic inflammation as a biomarker of seizure propensity and a target for treatment to reduce seizure propensity

et al. 2023

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People with diabetes can wear a device that measures blood glucose and delivers just the amount of insulin needed to return the glucose level to within bounds.Currently, people with epilepsy do not have access to an equivalent wearable device that measures a systemic indicator of an impending seizure and delivers a rapidly acting medication or other intervention (e.g., an electrical stimulus) to terminate or prevent a seizure. Given that seizure susceptibility is reliably increased in systemic inflammatory states, we propose a novel closed-loop device where release of a fast-acting therapy is governed by sensors that quantify the magnitude of systemic inflammation. Here, we review the evidence that patients with epilepsy have raised levels of systemic indicators of inflammation than controls, and that some anti-inflammatory drugs have reduced seizure occurrence in animals and humans. We then consider the options of what might be incorporated into a responsive anti-seizure system.

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“…2 EEG is a highly tedious, laborious, and time-consuming method for neurologists to identify seizures. 17,46 As continued analysis is required for the interpretation of results, hence, it is necessary to use video-EEG so that the scientists can determine when status epilepticus starts and when it stops. 31,47 Additionally, other stages like latent and chronic periods can also be determined through video-EEG.…”

Section: Experimental Interpretation Techniquesmentioning

confidence: 99%

Temporal lobe epilepsy with hippocampus sclerosis: prevalence, etiology, and treatment options with herbal medicines

Wasim

Musani

Siddiqi

et al. 2023

PJNS

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Background and objectives: Epilepsy is a neurological disorder in which the patient suffers with two or more unprovoked seizures. It is one of the most common neurological disorders worldwide, affecting more than 70 million people. Currently various modes of effective treatments are available, but still there are many cases that remain drug resistant. Hence, there is a need to explore herbal medications for the treatment of drug resistant epilepsy. Methods: Recent reviews and research articles (2000-2022) from PubMed and Google Scholar have been explored. Review: Based on etiology, there are six categories of epilepsy: Genetic, structural, metabolic, immune, infectious, and unknown epilepsy. Temporal lobe epilepsy with hippocampus sclerosis (TLE-HS) is one of the most common forms of structural epilepsy. Even though several new anti-epileptic drugs (AEDs) have been discovered, but the treatment of some cases especially TLE-HS remains resistant to them. Surgery is one of the most effective options for TLE-HS; however, this usually results in memory deficits, and occasionally, intracranial hematoma, delayed hydrocephalus, subdural empyema, and visual field defects in patients. Conclusion: Hence, to overcome drug resistance, new pharmacological and herbal therapies are required. Animal trials are first step in the development of new drugs, to study toxicity and efficacy of proposed drugs. Many herbs have anticonvulsant activity but remain an under-explored treatment option for epilepsy. Further research on herbal extracts as a possible treatment for epilepsy needs to be conducted.

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Minireview of Epilepsy Detection Techniques Based on Electroencephalogram Signals

Cited by 25 publications

References 62 publications

A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets

A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets

Systemic inflammation as a biomarker of seizure propensity and a target for treatment to reduce seizure propensity

Temporal lobe epilepsy with hippocampus sclerosis: prevalence, etiology, and treatment options with herbal medicines

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