April 2022
Intermediate to advanced
516 pages
22h 32m
English
book
Artificial Intelligence and Machine Learning for EDGE Computing
by Rajiv Pandey, Sunil Kumar Khatri, Neeraj Kumar Singh, Parul Verma
Content preview from Artificial Intelligence and Machine Learning for EDGE Computing
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Chapter 10: A study of deep learning approach for the classification of electroencephalogram (EEG) brain signals
Dharmendra Pathak; Ramgopal Kashyap; Surendra Rahamatkar Amity School of Engineering and Technology, Amity University Chhattisgarh, Raipur, Campus, India
Abstract
Electroencephalography (EEG) signals denote the electric activities of the brain. They are measured in microvolt (μV). There are various methods for the collection of raw data from these signals. Some of the important frequencies extracted from EEG signals are delta (frequency range: 0–4 Hz, mainly responsible for deep sleep, natural Healing, and immune system), theta (frequency range: 4–8 Hz, it represents creativity, emotional status, and relaxation), alpha (frequency ...
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