Analysis of EEG signals using Machine Learning for the Detection and Diagnosis of Epilepsy

Author:

Nagar Anubha, ,Bidushi ,Sarma Mimangsha,Kumar Mithra Anand,Valarmathi J., , , ,

Abstract

Electroencephalogram (EEG) is one of the most commonly used tools for epilepsy detection. In this paper we have presented two methods for the diagnosis of epilepsy using machine learning techniques. EEG waveforms have five different kinds of frequency bands. Out of which only two namely theta and gamma bands carry epileptic seizure information. Our model determines the statistical features like mean, variance, maximum, minimum, kurtosis, and skewness from the raw data set. This reduces the mathematical complexities and time consumption of the feature extraction method. It then uses a Logistic regression model and decision tree model to classify whether a person is epileptic or not. After the implementation of the machine learning models, parameters like accuracy, sensitivity, and recall have been found. The results for the same are analyzed in detail in this paper. Epileptic seizures cause severe damage to the brain which affects the health of a person. Our key objective from this paper is to help in the early prediction and detection of epilepsy so that preventive interventions can be provided and precautionary measures are taken to prevent the patient from suffering any severe damage

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Computer Science Applications,General Engineering,Environmental Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep Learning based Brain Tumor Detection with Internet of Things;2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS);2023-02-24

2. Machine Learning Approaches for Detecting Epileptic Seizures Based on Eeg Signals;2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon);2022-10-16

3. Brain Tumor Detection using Machine Learning Techniques with Internet of Things;2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon);2022-10-16

4. Classification and Analysis of Epileptic Seizure;2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET);2022-09-22

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