scholarly journals Is So Called “Split Alpha” in EEG Spectral Analysis a Result of Methodological and Interpretation Errors?

2020 ◽  
Vol 14 ◽  
Author(s):  
Ewa Zalewska
Keyword(s):  
Spectral Analysis ◽  
Time Window ◽  
Frequency Resolution ◽  
Eeg Signal ◽  
Eeg Spectral Analysis ◽  
Spectral Leakage ◽  
Eeg Spectrum ◽  
Interpretation Errors ◽  
Signal Dependence ◽  
Short Signal

This paper attempts to explain some methodological issues regarding EEG signal analysis which might lead to misinterpretation and therefore to unsubstantiated conclusions. The so called “split-alpha,” a “new phenomenon” in EEG spectral analysis described lately in few papers is such a case. We have shown that spectrum feature presented as a “split alpha” can be the result of applying improper means of analysis of the spectrum of the EEG signal that did not take into account the significant properties of the applied Fast Fourier Transform (FFT) method. Analysis of the shortcomings of the FFT method applied to EEG signal such as limited duration of analyzed signal, dependence of frequency resolution on time window duration, influence of window duration and shape, overlapping and spectral leakage was performed. Our analyses of EEG data as well as simulations indicate that double alpha spectra called as “split alpha” can appear, as spurious peaks, for short signal window when the EEG signal being studied shows multiple frequencies and frequency bands. These peaks have no relation to any frequencies of the signal and are an effect of spectrum leakage. Our paper is intended to explain the reasons underlying a spectrum pattern called as a “split alpha” and give some practical indications for using spectral analysis of EEG signal that might be useful for readers and allow to avoid EEG spectrum misinterpretation in further studies and publications as well as in clinical practice.

scholarly journals Spectral Analysis of Stationary Signals Based on Two Simplified Arrangements of Chirp Transform Spectrometer

Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 65
Author(s):  
Quan Zhao ◽  
Ling Tong ◽  
Bo Gao
Keyword(s):  
Spectral Analysis ◽  
Frequency Conversion ◽  
Frequency Resolution ◽  
Matching Problem ◽  
System Sensitivity ◽  
Deep Space Exploration ◽  
Spectrum Measurement ◽  
Stationary Signals ◽  
Simulation And Experiment ◽  
Remote Sensing Systems

The classical two-channel push-pull chirp transform spectrometer (CTS) has been widely applied in satellite-borne remote sensing systems for earth observation and deep space exploration. In this paper, we present two simplified structures with single M(l)-C(s) CTS arrangements for the spectral analysis of stationary signals. A simplified CTS system with a single M(l)-C(s) arrangement and a time delay line was firstly developed. Another simplified structure of CTS with a M(l)-C(s) arrangement and a frequency conversion channel was also developed for spectral analysis of stationary signals. Simulation and experiment results demonstrate that the two simplified arrangements can both realize spectrum measurement for the stationary signals and obtain the same frequency resolution, amplitude accuracy and system sensitivity as that of the classical two-channel push–pull CTS system. Compared to the classical CTS structure, the two simplified arrangements require fewer devices, save power consumption and have reduced mass. The matching problem between the two channels can be avoided in the two simplified arrangements. The simplified CTS arrangements may have potential application in the spectrum measurement of stationary signals in the field of aviation and spaceflight.

EEG spectral analysis after minor head injury in man

1988 ◽  
Vol 70 (2) ◽  
pp. 185-189 ◽  
Author(s):  
M.T. Tebano ◽  
M. Cameroni ◽  
G. Gallozzi ◽  
A. Loizzo ◽  
G. Palazzino ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Head Injury ◽  
Minor Head Injury ◽  
Eeg Spectral Analysis

An Adaptive Graph Spectral Analysis Method for Feature Extraction of an EEG Signal

2019 ◽  
Vol 19 (5) ◽  
pp. 1884-1896 ◽  
Author(s):  
Shanzhi Xu ◽  
Hai Hu ◽  
Linhong Ji ◽  
Peng Wang
Keyword(s):  
Feature Extraction ◽  
Spectral Analysis ◽  
Eeg Signal ◽  
Analysis Method ◽  
Spectral Analysis Method

Toward High-Resolution Mechanical Spectroscopy HRMS - Logarithmic Decrement

2012 ◽  
Vol 184 ◽  
pp. 467-472 ◽  
Author(s):  
Leszek B. Magalas ◽  
M. Majewski
Keyword(s):  
High Resolution ◽  
Low Frequency ◽  
Logarithmic Decrement ◽  
Frequency Resolution ◽  
Mechanical Spectroscopy ◽  
Spectral Leakage ◽  
Experimental Noise ◽  
Relative Errors ◽  
The Way

In this work, we present the comparison between different methods used to compute the logarithmic decrement,δ. The parametric OMI method and interpolated DFT (IpDFT) methods are used to compute theδfrom free decaying oscillations embedded in an experimental noise typical for low-frequency mechanical spectrometers. The results are reported forδ= 5×10-4, = 1.12345 Hz and different sampling frequencies, = 1 kHz and 4 kHz. A new YM algorithm yields the smallest dispersion in experimental points of the logarithmic decrement and the smallest relative errors among all investigated IpDFT methods. In general, however, the IpDFT methods suffer from spectral leakage and frequency resolution. Therefore it is demonstrated that the performance of different methods to compute theδcan be listed in the following order: (1) OMI, (2) YM, (3) YMC, and (4) the Yoshida method, Y. For short free decays the order of the best performers is different: (1) OMI and (2) YMC. It is important to emphasize that IpDFT methods (including the Yoshida method, Y) are discouraged for signals that are too short. In conclusion, the best methods to compute the logarithmic decrement are the OMI and the YM. These methods will pave the way toward high-resolution mechanical spectroscopy HRMS.

Sign in / Sign up

Export Citation Format

Share Document