Comparative Assessment of Spectral Analysis Methods for Characterizing Forced Oscillation

Author(s):  
Priya Singh ◽  
Abhineet Prakash ◽  
Kundan Kumar ◽  
S. K. Parida
2022 ◽  
Author(s):  
Maria Semeli Frangopoulou ◽  
Maryam Alimardani

Alzheimers disease (AD) is a brain disorder that is mainly characterized by a progressive degeneration of neurons in the brain, causing a decline in cognitive abilities and difficulties in engaging in day-to-day activities. This study compares an FFT-based spectral analysis against a functional connectivity analysis based on phase synchronization, for finding known differences between AD patients and Healthy Control (HC) subjects. Both of these quantitative analysis methods were applied on a dataset comprising bipolar EEG montages values from 20 diagnosed AD patients and 20 age-matched HC subjects. Additionally, an attempt was made to localize the identified AD-induced brain activity effects in AD patients. The obtained results showed the advantage of the functional connectivity analysis method compared to a simple spectral analysis. Specifically, while spectral analysis could not find any significant differences between the AD and HC groups, the functional connectivity analysis showed statistically higher synchronization levels in the AD group in the lower frequency bands (delta and theta), suggesting that the AD patients brains are in a phase-locked state. Further comparison of functional connectivity between the homotopic regions confirmed that the traits of AD were localized in the centro-parietal and centro-temporal areas in the theta frequency band (4-8 Hz). The contribution of this study is that it applies a neural metric for Alzheimers detection from a data science perspective rather than from a neuroscience one. The study shows that the combination of bipolar derivations with phase synchronization yields similar results to comparable studies employing alternative analysis methods.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 873 ◽  
Author(s):  
Flóra Pomázi ◽  
Sándor Baranya

The monitoring of fluvial suspended sediment transport plays an important role in the assessment of morphological processes, river habitats, or many social activities associated with river management. However, establishing and operating a well-functioning sediment monitoring system requires the involvement of advanced indirect methods. This study investigates the advantages and limitations of optical and acoustic devices, to quantify the uncertainties and provide a comprehensive comparative assessment of the investigated indirect methods. The novelty of this study, compared to previous ones, is that four different indirect techniques are parallel tested, i.e., the laser diffraction based LISST-Portable|XR, an infrared based optical instrument, the VELP TB1 turbidimeter, the acoustic based LISST-ABS (Acoustical Backscatter Sensor) sensor, and a 1200 kHz Teledyne RD Instruments Acoustic Doppler Current Profiler (ADCP). The calibration of all the indirect methods was performed based on more than 1000 samples taken from the Hungarian section of the Danube River within a wide suspended sediment concentration range. Implementing a comparative assessment of the different sediment analysis methods, a qualitative and quantitative characterisation of the applicability is provided. Furthermore, a proposal for an optimised sediment monitoring methodology is also suggested.


2013 ◽  
Vol 5 (1) ◽  
pp. 29-36 ◽  
Author(s):  
S Paul ◽  
P Bhattacharya ◽  
AK Pandey ◽  
N Sharma ◽  
JP Tiwari ◽  
...  

The present work envisages mathematical modeling of induced focal cerebral ischemia in animal model using EEG data with the help of Fast Fourier Transformation method. Amongst several analysis methods, spectral analysis methods are important because it detects the frequencies and characteristics changes of brain waveforms depending on the brain function affected from disorders and physiological state. There are many applications of FFT, and the most important being that it is one of the basic conventional spectral analysis methods. However, it has some limitations, for instance, it adds contributions in the low frequency region which are not present in the original signal, and necessitates the use of windowing for decreasing the error rate. The present analysis was undertaken to ensure actual correlation of the different mathematical paradigms. EEG data were obtained from different regions of rat brain and were processed by FFT modeling in MATLAB platform. The assessment of long lasting functional outcome and to prevalent classical approach to study stroke was necessitated and therefore highly recommended to evaluate the efficacy of therapeutic strategies in relation to EEG in animal model of brain stroke. This mathematical modeling specifically Power Spectrum Density analysis was done to correlate the different prevalent condition of rat brain function. DOI: http://dx.doi.org/10.3329/bjmp.v5i1.14666 Bangladesh Journal of Medical Physics Vol.5 No.1 2012 29-36


2012 ◽  
Vol 102 (5) ◽  
pp. 1144-1153 ◽  
Author(s):  
David Valdman ◽  
Paul J. Atzberger ◽  
Dezhi Yu ◽  
Steve Kuei ◽  
Megan T. Valentine

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