Short-time Fourier Transform analysis of EEG signal from writing

Short-time Fourier Transform (STFT) provides an advantage of revealing the frequency contents of the signal at each time point in the signal. This information can be used to provide control and perform several tasks in Brain Computer Interface system. This paper describes the STFT analysis of EEG signals obtained during relaxing and writing, The results of the STFT analysis showed that there are significant differences in the frequency components and patterns between the EEG signals obtained from relax and writing.

[1]  Irena Koprinska,et al.  Classification of Brain-Computer Interface Data , 2008, AusDM.

[2]  F. L. D. Silva,et al.  EEG signal processing , 2000, Clinical Neurophysiology.

[3]  Joerg F. Hipp,et al.  Time-Frequency Analysis , 2014, Encyclopedia of Computational Neuroscience.

[4]  Syed M. Saddique,et al.  EEG Based Brain Computer Interface , 2009, J. Softw..

[5]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[6]  Yan Guozheng,et al.  EEG feature extraction based on wavelet packet decomposition for brain computer interface , 2008 .

[7]  G. Pfurtscheller,et al.  On the existence of different types of central beta rhythms below 30 Hz. , 1997, Electroencephalography and clinical neurophysiology.

[8]  Heikki Lyytinen,et al.  Psychophysiology of developmental dyslexia: a review of findings including studies of children at risk for dyslexia , 2005, Journal of Neurolinguistics.

[9]  Emmanuel Ifeachor,et al.  Digital Signal Processing: A Practical Approach , 1993 .

[10]  Cuntai Guan,et al.  A clinical evaluation on the spatial patterns of non-invasive motor imagery-based brain-computer interface in stroke , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  W. Mansor,et al.  An analysis of EEG signal generated from grasping and writing , 2011, 2011 IEEE International Conference on Computer Applications and Industrial Electronics (ICCAIE).

[12]  P PaulrajM,et al.  An Analysis of the Effect of EEG Frequency Bands on the Classification of Motor Imagery Signals , 2011 .