The classification of EEG signal processing using different machine learning techniques for BCI application
Brain-Computer Interface (BCI) or Human-Machine Interface is now becoming vital in biomedical engineering and technology field which applying EEG technologies to provide assistive device technology (AT) to humans. Hence, this paper presents the results of analyzing EEG signals from various human cog...
Main Authors: | Rashid, Mamunur, Norizam, Sulaiman, Mahfuzah, Mustafa, Sabira, Khatun, Bari, Bifta Sama |
---|---|
Format: | Conference or Workshop Item |
Language: | English English |
Published: |
Springer, Singapore
2019
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/24498/ http://umpir.ump.edu.my/id/eprint/24498/ http://umpir.ump.edu.my/id/eprint/24498/1/29.%20The%20classification%20of%20EEG%20signal%20processing%20using%20different.pdf http://umpir.ump.edu.my/id/eprint/24498/2/29.1%20The%20classification%20of%20EEG%20signal%20processing%20using%20different.pdf |
Similar Items
-
Analysis of EEG features for brain computer interface application
by: Rashid, Mamunur, et al.
Published: (2019) -
Recent Trends and Open Challenges in EEG based Brain-Computer Interface Systems
by: Rashid, Mamunur, et al.
Published: (2019) -
Classification of EEG Signal for Body Earthing Application
by: Noor Aisyah , Ab Rahman, et al.
Published: (2017) -
Classification of EEG Spectrogram Using ANN for IQ Application
by: Mahfuzah, Mustafa, et al.
Published: (2013) -
Wink based facial expression classification using machine learning approach
by: Rashid, Mamunur, et al.
Published: (2020)