I worked on using machine learning to classify alzheimer's vs healthy controls using EEG signals. The features used were magnitudes of FFT and CWT over various frequency bands and have obtained some very good results as well.

Hello. You can check this page https://data.world/ or also the UCI web psge.

Pholpat Durongbhan i have done cwt, i am bit confused how to feed this to machine learning algorithm

Try find in articles:

https://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Continuous+EEG+signal+analysis+for+asynchronous+BCI+application#0

Article Parametric and Nonparametric EEG Analysis for the Evaluation...

Article Multivariate Multi-Scale Permutation Entropy for Complexity ...

HTH

You might be interested in:

1. Astolfi, Laura; Toppi, Jlenia; Borghini, Gianluca; Vecchiato, Giovanni; Isabella, R.; Vico Fallani, Fabrizio de et al.: Study of the functional hyperconnectivity between couples of pilots during flight simulation. An EEG Hyperscanning Study. In: IEEE Eng Med Biol Soc., Bd. 2011, S. 2338–2341. Online verfügbar unter http://ieeexplore.ieee.org/servlet/opac?punumber=6067544.

2. Astolfi, Laura; Toppi, Jlenia; Vico Fallani, Fabrizio de; Cincotti, Febo; Wilke, Christopher T.; Yuan, Han et al. (2011): Methods for the EEG Hyperscanning. Simultaneous Recordings from Multiple Subjects during Social Interaction. In: 2011 8th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the 2011 8th International Conference on Bioelectromagnetism. Online verfügbar unter http://ieeexplore.ieee.org/servlet/opac?punumber=5910695.

3. Fukuda, Haruaki; Shiomi, Masahiro; Nakagawa, Kayako; Ueda, Kazuhiro (2012): 'Midas touch' in human-robot interaction. New York, NY: ACM. Online verfügbar unter http://dl.acm.org/citation.cfm?id=2157689.

4. Nakamura, Tsukasa; Tomita, Yohei; Ito, Shin-ichi; Mitsukura, Yasue (2010): A method of obtaining sense of touch by using EEG. 19th IEEE International Symposium on Robot and Human Interactive Communication ; 13 - 15 Sept. 2010, Viareggio, Italy. Piscataway, NJ: IEEE. Online verfügbar unter http://ieeexplore.ieee.org/servlet/opac?punumber=5593942.