Abstract
Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes’ movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes’ movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes’ movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method.
Highlights
FNIRS is a non-invasive optical methodology able to measure cortical oscillation of oxygenated (O2 Hb) and deoxygenated (HHb) hemoglobin related to neuronal activity through the blood oxygen level dependent (BOLD) effect [1,2,3]
The tracking procedure allowed us to estimate the motion of the optodes and to evaluate, by means of continuous wavelet transform (CWT) and wavelet coherence (WCOH), its influence on the Functional near infrared spectroscopy (fNIRS) signals
The results demonstrated that the proposed method increases the capability of the GLM based approach to assess the cortical activation, demonstrating its effectiveness in improving the statistical analysis of the fNIRS
Summary
FNIRS is a non-invasive optical methodology able to measure cortical oscillation of oxygenated (O2 Hb) and deoxygenated (HHb) hemoglobin related to neuronal activity through the blood oxygen level dependent (BOLD) effect [1,2,3] This technique is portable, relatively cheap, lightweight and quite resilient to motion artifacts with a mechanical structure resembling electroencephalography (EEG) [4,5], being suitable for ecological measurements, such as the clinical practice and outdoor applications [6,7,8,9]. Motion artifacts usually produce high-frequency noise overlapped to the functional hemodynamic signal, but, when the optodes–scalp coupling is definitely compromised, they could provoke a lasting shift. Movement artifacts may generate both high- and low-frequency components that cannot be removed by frequency filtering
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