WU-NEAT: A clinically validated, open-source MATLAB toolbox for limited-channel neonatal EEG analysis

Abstract

Background: Limited-channel EEG research in neonates is hindered by lack of open, accessible analytic tools. To overcome this limitation, we have created the Washington University-Neonatal EEG Analysis Toolbox (WU-NEAT), containing two of the most commonly used tools, provided in an open-source, clinically-validated package running within MATLAB. Methods:The first algorithm is the amplitude-integrated EEG (aEEG), which is generated by filtering, rectifying and time-compressing the original EEG recording, with subsequent semilogarithmic display. The second algorithm is the spectral edge frequency (SEF), calculated as the critical frequency below which a user-defined proportion of the EEG spectral power is located. The aEEG algorithm was validated by three experienced reviewers. Reviewers evaluated aEEG recordings of fourteen preterm/term infants, displayed twice in random order, once using a reference algorithm and again using the WU-NEAT aEEG algorithm. Using standard methodology, reviewers assigned a background pattern classification. Inter/intra-rater reliability was assessed. For the SEF, calculations were made using the same fourteen recordings, first with the reference and then with the WU-NEAT algorithm. Results were compared using Pearson's correlation coefficient.Results: For the aEEG algorithm, intra-and inter-rater reliability was 100% and 98%, respectively. For the SEF, the mean±SD Pearson correlation coefficient between algorithms was 0.96±0.04. Conclusion:We have demonstrated a clinically-validated toolbox for generating the aEEG as well as calculating the SEF from EEG data. Open-source access will enable widespread use of

Wavelet-based neurovascular coupling can predict brain abnormalities in neonatal encephalopathy

“…For this specific study, the time series of EEG from a cross-hemisphere electrode pair of C3 and C4 (i.e., two electrodes in the central region) were used for data analysis of all the neonates. The EEG data from C3-C4 channel pair were first passed through an asymmetric band-pass filter (Parks-McClellan linear-phase FIR filter), which strongly attenuated the signal below 2 Hz and above 15 Hz, followed by conversion to aEEG using Washington University-Neonatal EEG Analysis Toolbox (WU-NEAT) ( Vesoulis et al, 2020 , Das et al, 2020 ). Artificial spikes from aEEG data were first detected and interpolated with neighboring data points.…”

Neurovascular coupling (NVC) in newborns using processed EEG versus amplitude-EEG

“…1 a shows a temporal trace of 5-h, 256-Hz raw EEG signal, after bandpass filtering (0.1–100 Hz) and rectification, from a normal reference control neonate (Neonate #1). Figure 1 b shows an aEEG tracing derived using WU-NEAT method (black trace) 7 together with a three-step processed EEG (gray trace), both derived from the original EEG signal (i.e., Fig. 1 a).…”

“…The y-axis represents amplitude of raw EEG in μV, plotted with a linear scale, while x-axis represents time in minute. ( b ) Three-step processed EEG tracing (processed EEG, gray trace) plotted together with aEEG (black trace) derived with WU-NEAT 7 . The y-axis represents amplitude of aEEG or processed EEG in μV, plotted with a linear scale between 0–10 μV and a log scale for any value larger than 10 μV.…”

“…Top and bottom rows correspond to WTC-based SctO2-aEEG and SctO2-processed EEG coherence (R 2 ), R SctO2→aEEG and R SctO2→processed EEG , for each case (Neonate #: N1-N8). For each panel of the top row, aEEG tracings were derived using WU-NEAT method 7 ; for each panel of the bottom row, processed EEG tracings were obtained by three-step preprocessing means: bandpass filtering (2–15 Hz), rectifying, and down sampling (0.21 Hz) on processed EEG tracings. …”

“…The raw EEG was converted to amplitude-EEG using neonatal EEG analysis toolbox (WU-NEAT) from Washington university, which is an open-source, MATLAB-compatible, clinically validated toolbox to quantify aEEG 7 and has been described as Method 2 in our prior study 6 .…”