Abstract
Nowadays, brain function evaluation using Functional Near Infrared Spectroscopy (fNIRS) is one of the most potential non-invasive monitoring techniques. This paper concerns usefulness of the NIRS signals denoising using the Hemodynamic Evoked Response (HomER) as graphical user interface displays the NIRS data, fast independent component analysis (FASTICA) method to reduce data dimension and the combined Wavelet & PCA method for enhancing NIRS signals. NIRS signals include many types of noise, spread across a broad spectrum of frequencies, such as: low frequency noise from respiratory interference, 0.1 - 0.3 Hz, Mayer wave, about 0.1 Hz, cardiac interference, 0.8 - 2.0 Hz, and other artifacts from head and facial motions. Meanwhile, electronic components generate high frequency noise. Multi-resolution wavelet and PCA was applied successfully to enhance the NIRS signals. It consists of adaptively modifying the wavelet coefficients based on the degree of noise contamination of the processed NIRS signal. This is done subsequently to the signal pre-processing by reducing data dimension using the FASTICA method. We demonstrate, using signal-to-noise ratio and correlation indicators, that the technique used is superior to the wavelet and moving average filter and outperforms the proposed denoising NIRS signal.
Highlights
NIRS is a new medical device that can be used for long term monitoring of brain activity in several diseases of the human brain
While many techniques exist for creating NIRS signals, in our work, we focus on optical measurement by continuous wave (CW)
We presented a new algorithm dedicated to processing NIRS signals based on Hemodynamic Evoked Response (HomER) toolbox for extracting NIRS signals, a fast independent component analysis (FASTICA) method for reducing NIRS data, and Wavelet & PCA for efficiently denoising NIRS signals, while all sub-algorithms used Matlab v. 2012a
Summary
NIRS is a new medical device that can be used for long term monitoring of brain activity in several diseases of the human brain. Several laboratories have focused on NIRS for functional imaging. Among the most common methods used in the clinical setting are the traditional methods of magnetic resonance imaging (MRI) and positron emission tomography (PET). NIRS is a new technique in the medical imaging field. How to cite this paper: Chaddad, A. (2014) Brain Function Diagnosis Enhanced Using Denoised fNIRS Raw Signals. J. Biomedical Science and Engineering, 7, 218-227.
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