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Results for “Spectrum Analysis”

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At least 181 records · Page 10Linked to original sources
PubMed1989

[Spectrum analysis of blood pressure and cardiac rate in the conscious rat].

Intrafemoral pulsatile blood pressure of conscious rats was computed to generate evenly spaced signals (systolic, diastolic, mean blood pressure, heart rate) at 200 ms intervals. This equidistant sampling allowed a direct spectral analysis using a Fast Fourier Transform algorithm. Systolic blood pressure and heart rate exhibited low frequency oscillations (Mayer waves, 20-605 mHz) and a high frequency peak related to respiration (1,765 mHz). The diastolic blood pressure and the mean blood pressure only exhibited low frequency oscillations. This procedure could be useful to analyze the various components of blood pressure variability.

Analysis of Variance↗
PubMed2005

Integrated study of topographical functional maps based on an auditory comprehension paradigm using an eigensystem study and spectrum analysis.

This study integrates a spectral analysis of key frequency bands (Alpha, Beta, Delta, and Theta) with an eigensystem-based study in order to validate brain functional mappings associated with the characterization effects of an Auditory/Comprehension paradigm. This numerical characterization supported by topographic functional maps brings added insight in the involvement of the Wernicke and Broca's brain areas to language comprehension. A thorough examination of EEG recordings through the eigensystem reveals that eigenvectors associated with the largest eigenvalues produce an interesting activity pattern located in the frontal area of the brain directly attributable to those characteristic behaviors found in the Alpha, Beta, Delta, and Theta frequency bands. An evaluation of spectral arrays is performed using topographic maps of the induced brain activities during both listening and answering phases. This evaluation is then augmented with quantifying measures using the eigensystem study while results are validated through integration of EEG activity and eigensystem modalities. Such a representation can provide insightful information on how different patients react during an auditory and response phases, and in the ability to detect the presence of potential neurological disorders by assessing similar/dissimilar behaviors with respects to all former patients already included in the database. The algorithm as developed in this study could be extended in its application to other brain functional mapping tasks given its simple but effective practical mathematical foundation.

Acoustic Stimulation↗