Low Frequency Noise Remove from EEG Signal
Awnish Kumar1, Rahul Tiwari2, Abhilash Gaur3

1Awnish Kumar, Student, B. Tech, Electronics and communication Engineering from Galgotias University, Greater Noida, Uttar Pradesh, India.
2Rahul Tiwari , Student, B. Tech, Electronics and communication Engineering from Galgotias University, Greater Noida, Uttar Pradesh, India.
3Abhilash Gaur, Assistant Professor, Electrical, Electronics and Communication Engineering, Galgotias University, Greater Noida, India.

Manuscript received on April 30, 2020. | Revised Manuscript received on May 06, 2020. | Manuscript published on May 30, 2020. | PP: 1510-1513 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2456059120/2020©BEIESP | DOI: 10.35940/ijrte.A2456.059120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The electrical activity of the brain recorded by EEG which used to detect different types of diseases and disorders of the human brain. There is contained a large amount of random noise present during EEG recording, such as artifacts and baseline changes. These noises affect the low -frequency range of the EEG signal. These artifacts hiding some valuable information during analyzing of the EEG signal. In this paper we used the FIR filter for removing low -frequency noise(<1Hz) from the EEG signal. The performance is measured by calculating the SNR and the RMSE. We obtained RMSE average value from the test is 0.08 and the SNR value at frequency(<1Hz) is 0.0190. 
Keywords: EEG data , Artifact , noise, RMSE, SNR.
Scope of the Article: Frequency Selective Surface