@inproceedings{e7fb80d4ed594f69a4c7c2271b277496,
title = "Artifact removal for physiological signals via wavelets",
abstract = "In order to analyze brain activity signals, it is important to remove any artifact of the obtained data so that we can further provide diagnosis of possible symptoms. There are many different ways to do denoising of the given signals. In this paper, we test several biosignals and obtain an optimal ways to denoise the data and perform time frequency analysis of an EEG signal.",
keywords = "Artifact removal, EEG, FNIRS, Multiresolution analysis., Physiological signal, Wavelet transform",
author = "Lin, {En Bing} and Oluremi Abayomi and Keshab Dahal and Patrick Davis and Mdziniso, {Nonhle Channon}",
note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; null ; Conference date: 20-05-2016 Through 23-05-2016",
year = "2016",
doi = "10.1117/12.2244906",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Xudong Jiang and Falco, {Charles M.}",
booktitle = "Eighth International Conference on Digital Image Processing, ICDIP 2016",
}