An epileptic seizures detection algorithm based on the empirical mode decomposition of EEG
Lorena Orosco1, Eric Laciar, Agustina Garces Correa
1Gabinete de Tecnología Médica, Universidad Nacional de San Juan, San Juan, Argentina. lorosco@gateme.unsj.edu.ar
Summary
This study introduces an automatic epileptic seizure detection algorithm using Empirical Mode Decomposition (EMD). The method analyzes electroencephalogram (EEG) energy to identify seizures, showing promise for epilepsy diagnosis.
Area of Science:
- Neurology
- Biomedical Engineering
- Signal Processing
Background:
- Epilepsy affects 50 million globally, necessitating accurate seizure detection for diagnosis.
- Current diagnostic methods rely on precise seizure identification from neurological signals.
Purpose of the Study:
- To develop an automated epileptic seizure detection algorithm.
- To evaluate the efficacy of the Empirical Mode Decomposition (EMD) method for this purpose.
Main Methods:
- Computed Intrinsic Mode Functions (IMFs) from electroencephalogram (EEG) records.
- Calculated IMF energy and applied thresholding with minimum duration criteria for detection.
- Validated the algorithm on invasive EEG data from epilepsy patients.
Main Results:
- The algorithm achieved a sensitivity of 56.41% and a specificity of 75.86% in analyzed segments.
- Tested on 90 segments, including 39 with epileptic seizures.
Conclusions:
- Empirical Mode Decomposition (EMD) shows potential as a method for automatic epileptic seizure detection in EEG.
- Further refinement may improve the performance of EMD-based seizure detection systems.
Related Concept Videos
01:24Epilepsy and Seizures: Overview
Epilepsy is a chronic neurological disease marked by recurrent, unpredictable seizures. These seizures are caused by abnormal electrical discharges in the brain, leading to behavior, sensation, or consciousness alterations. They can also cause transient impairment of awareness, interfering with daily activities.
Various factors can trigger epilepsy, including genetic factors, brain damage, metabolic causes, and unknown etiology. Diagnosis of epilepsy involves electroencephalography (EEG), which...
Various factors can trigger epilepsy, including genetic factors, brain damage, metabolic causes, and unknown etiology. Diagnosis of epilepsy involves electroencephalography (EEG), which...
01:13Seizures: Classification
Epilepsy is primarily characterized by unpredictable seizures, either provoked by an identifiable factor, such as injury or illness, or unprovoked, occurring spontaneously without apparent cause.
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types:
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types: