Patient Specific Seizure Onset-Offset Latency Detection using Long- term EEG Signals

Chandel, Garima; Farooq, Omar; Khan, Yusuf Uzzaman; Varshney, Yash Vardhan

doi:10.1109/upcon47278.2019.8980068

Cited by 4 publications

References 21 publications

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Automatic detection of ictal activity in EEG using synchronization and chaos-based attributes

Mahgoub,

Qaraqe

2023

Med Biol Eng Comput

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Automatic seizure onset detectors (SODs) have been proposed to alert epileptic patients when a seizure is about to happen and in turn improve their quality of life. Yet, the detectors proposed in literature are complex and difficult to implement in real-time as they utilize large feature sets with redundant and irrelevant features. Hence, the aim of this work is to propose a simple and lightweight SOD that exploits two characteristics that reflect the neuronal behavior during a seizure. Namely, the synchronization between EEG channels and the chaoticity of the EEG; synchronization was measured by the condition number while the recurrence period density entropy estimated the chaoticity of an EEG signal. A support vector machine was trained and tested on 10 patients from a scalp EEG dataset and was able to detect the considered seizures with a sensitivity of 100% and a false positives rate of 0.5 per hour. The results indicate that synchronization and chaos attributes can reflect the manifestation of seizures in EEG data and can be used to develop SODs. This work emphasizes that even a single relevant feature can produce an SOD with comparable performance to SODs that use many features. Graphical Abstract

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Automatic detection of ictal activity in EEG using synchronization and chaos-based attributes

Mahgoub,

Qaraqe

2023

Med Biol Eng Comput

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A unified multi-level spectral–temporal feature learning framework for patient-specific seizure onset detection in EEG signals

Tang

Liu

et al. 2020

Knowledge-Based Systems

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Automatic Detection of Ictal Activity in EEG Channels using Synchronization Attributes

Mahgoub

Qaraqe

2021

2020 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)

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Patient Specific Seizure Onset-Offset Latency Detection using Long- term EEG Signals

Cited by 4 publications

References 21 publications

Automatic detection of ictal activity in EEG using synchronization and chaos-based attributes

Automatic detection of ictal activity in EEG using synchronization and chaos-based attributes

A unified multi-level spectral–temporal feature learning framework for patient-specific seizure onset detection in EEG signals

Automatic Detection of Ictal Activity in EEG Channels using Synchronization Attributes

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