EEG Data Sets Signal Processing Using Wavelet Transforms
S. D. Bhagwat1, Vinod Jain2

1Dr. S. D. Bhagwat, Senior Professor and Head, Department of Electronics, Mukesh Patel Technology, Management and Engineering, SVLM’s NMIMS, Mumbai (Maharashtra), India.
2Prof. Vinod Jain, Department of Electronics, Mukesh Patel Technology, Management and Engineering, NMIMS, Mumbai (Maharashtra), India.
Manuscript received on 10 May 2013 | Revised Manuscript received on 18 May 2013 | Manuscript Published on 30 May 2013 | PP: 108-111 | Volume-2 Issue-6, May 2013 | Retrieval Number: F0810052613/13©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Sensing is fundamental to all measurements, and its quality depends on many factors such as size, material used, etc. Physiological sensors measure core body temperature, ambulatory blood pressure, blood oxygen etc. Sensitive medical equipment EEG (Electroencephalography) measures electricity levels over areas of the human brain scalp. Data acquisition and processing of these voltages and signals involves lot of processing time. It is possible to expand the signal in a series of wavelets. Then we can join the advantages of the wavelet transform with the atomic decomposition of signal. Wavelet analysis provides a timescale description of any finite energy signal. Essentially, it is a successive decomposition of the signal in different scales. At each step, the corresponding details are separated, providing useful information for detecting and characterizing short time phenomena or abrupt changes of energy. This paper studies wavelet transforms for EEG data processing.
Keywords: Sensor, EEG, Neurological Disorder, Wavelets.

Scope of the Article: Signal and Speech Processing