Classification of EEG signals using machine learning and deep learning techniques
نویسندگان
چکیده
Electroencephalogram (EEG) signals reveal electrical activity of brain in a person. Brain cells interact by impulses even during sleep. Any disruptions to these induce problems the individual. Hence clinicians analyze EEG readings comprehend impulses. and its sub bands depict pattern human brain. data comprises transient components, spikes, other sorts artifacts due eye blinking, movement individual, anxiousness etc. collection. Wavelet transformations are effective mathematical technique for sampling approximation produce clear EEG. It also assists filtering, sampling, interpolation, noise reduction, signal augmentation, feature extraction. In this study, survey is done on motor imagery various classifiers assess them machine learning methods categorization studied. Conventional SVM logistic regression combined with basic 2-layer Neural Network (NN) constructed using python keras performances.
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ژورنال
عنوان ژورنال: International Journal of Health Sciences (IJHS)
سال: 2022
ISSN: ['2550-6978', '2550-696X']
DOI: https://doi.org/10.53730/ijhs.v6ns1.7595