Preprocessing of fNIRS data was performed using Homer2 toolbox in Matlab 2013a (MathWorks Inc.). Noisy channels and unrelated time periods were manually identified and removed prior to converting the data into optical density data. Channels with motion artifacts were identified and corrected (Scholkmann et al., 2010 (link)), and removed by performing cubic spline interpolation. A 3th order Butterworth band-pass filter with cut-off frequencies of 0.01–0.1 Hz was then applied to remove artifacts, including cardiac interference (~1.3 Hz) and respiration (~0.25 Hz) (Pinti et al., 2018 (link)). Finally, the modified Beer–Lambert equation was used to convert the optical density data into HbO and HbR concentrations.
Homer2 toolbox
Manufactured by MathWorks
Sourced in United States
The Homer2 toolbox is a MATLAB-based software package that provides a set of tools for analyzing and visualizing data related to the hydrogen evolution reaction (HER). The toolbox includes functions for processing and analyzing electrochemical data, as well as tools for generating and customizing plots and figures.
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Lab products found in correlation
2 protocols using homer2 toolbox
1
fNIRS Data Preprocessing with Homer2
2
Cerebral Hemodynamics in Hand Grasp Tasks
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In this study, we adopted ∆HbO signals as the indicator of hemodynamic response because it is more sensitive than deoxyhemoglobin on regional cerebral blood flow (Strangman et al. 2002; Hoshi et al. 2001) (link). We preprocessed the fNIRS data offline using HomER2 toolbox in Matlab 2014a (The MathWorks Inc., USA) (Huppert et al. 2009 (link)). After raw intensity data was converted to optical density changes, the Spline interpolation algorithm was used to correct motion artifacts caused by head movements during data acquisition. Then, a bandpass filter between 0.01 Hz and 0.2 Hz was carried out to remove the effect of physiological noises and drifts. Finally, the optical density was converted to ∆HbO based on the modified Beer-Lambert law. The mean time for completing 10 repetitions in healthy participants was 16.1 (SD = 3.2) seconds, while 18.3 (SD = 4.6) seconds for patients with stroke.
Although participants practiced the pace of hand grasp before the experiment, they still completed 10 repetitions of movements 20 seconds earlier. Therefore, we cut a temporal window from -2 s to 16 s relative to the onset of movements (t = 0 s) for event averaging for healthy participants, while -2 s to 18 s for patients with stroke.
Although participants practiced the pace of hand grasp before the experiment, they still completed 10 repetitions of movements 20 seconds earlier. Therefore, we cut a temporal window from -2 s to 16 s relative to the onset of movements (t = 0 s) for event averaging for healthy participants, while -2 s to 18 s for patients with stroke.
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