Motion Artifacts Correction From EEG and fNIRS Signals Using Novel Multiresolution Analysis-Reference-Cited by-同舟云学术

Motion Artifacts Correction From EEG and fNIRS Signals Using Novel Multiresolution Analysis

Published:2022 Issue: Volume:10 Page:29760-29777
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hossain Md. Shafayet¹^ORCID,Reaz Mamun Bin Ibne¹^ORCID,Chowdhury Muhammad E. H.²^ORCID,Ali Sawal H. M.¹^ORCID,Bakar Ahmad Ashrif A.¹^ORCID,Kiranyaz Serkan²^ORCID,Khandakar Amith²^ORCID,Alhatou Mohammed³^ORCID,Habib Rumana⁴

Affiliation:

1. Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

2. Department of Electrical Engineering, Qatar University, Doha, Qatar

3. Department of Neurology, Neuromuscular Division, Al-Khor, Hamad General Hospital, Doha, Qatar

4. Department of Neurology, BIRDEM General Hospital, Dhaka, Bangladesh

Funder

Universiti Kebangsaan Malaysia

Qatar National Research Foundation

International Research Collaboration Co-Fund

Qatar National Library

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09733342.pdf?arnumber=9733342

Reference66 articles.

1. Singular-spectrum analysis: A toolkit for short, noisy chaotic signals

2. Motion artifact removal from single channel electroencephalogram signals using singular spectrum analysis

3. Artifact Removal in Physiological Signals—Practices and Possibilities

4. Methods for artifact detection and removal from scalp EEG: A review

5. Adaptive filtering of physiological noises in fNIRS data

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