Waveform and Frequency Spectra of Acoustic Emissions

1971 ◽  
Vol 49 (1A) ◽  
pp. 110-110
Author(s):  
Adrian A. Pollock ◽  
Raymond W. B. Stephens
Keyword(s):  
Acoustic Emissions ◽  
Frequency Spectra

Waveforms and Frequency Spectra of Acoustic Emissions

1971 ◽  
Vol 50 (3B) ◽  
pp. 904-910 ◽  
Author(s):  
R. W. B. Stephens ◽  
A. A. Pollock
Keyword(s):  
Acoustic Emissions ◽  
Frequency Spectra

Frequency spectra of cochlear acoustic emissions (’’Kemp‐echoes’’)

1981 ◽  
Vol 70 (2) ◽  
pp. 437-445 ◽  
Author(s):  
H. P. Wit ◽  
J. C. Langevoort ◽  
R. J. Ritsma
Keyword(s):  
Acoustic Emissions ◽  
Frequency Spectra

scholarly journals Singing sands, booming dune sands, and the stick–slip effect

2012 ◽  
Vol 90 (7) ◽  
pp. 611-631 ◽  
Author(s):  
A.J. Patitsas
Keyword(s):  
Shear Band ◽  
Shear Bands ◽  
Acoustic Emissions ◽  
Low Frequency ◽  
Dominant Frequency ◽  
Slip Effect ◽  
Dune Sand ◽  
Frequency Spectra ◽  
Stick Slip ◽  
Modes Of Vibration

The origin of the acoustic and seismic emissions from impacted singing grains and from avalanching dune sand grains is sought in modes of vibration in discreet grain columns. It is postulated that when the grains in a column are pressed together and forced to slide over one another, elastic shear bands are formed at the contact areas with distinct elastic moduli. Such contact shear bands would have implications in the formulation of the Hertz–Mindlin contact theory. The assembly of all grain columns below the impacting pestle forms the slip (slide) shear band. The transfer of energy from the pestle to the modes of vibration in such columns is effected by the stick–slip effect. The intense collective vibration of all columns in the slip shear band results in the familiar musical sound. The concept of grain flowability is used to justify the disparity between the acoustic emissions from impacted singing grains and from avalanching booming dune sand grains. The concept of grain columns is assumed to apply in the freely avalanching sand band, but with longer length to justify the lower frequencies. This approach predicts frequency spectra comprising a low-frequency content and a dominant frequency with its harmonics in agreement with the experimental evidence. Additionally, it can account for the low-frequency vibration evoked when booming sand flows through a funnel, with implications in the understanding of grain silo vibrations. It is argued that sand grains do not sing or boom because the stick–slip effect in not applicable in the contact shear bands.

Oto Acoustic Emissions (OAE): the shape-similarity of pure-tone audiogram and OAE-gram

1999 ◽  
Vol 24 (4) ◽  
pp. 377-383
Author(s):  
G. A. van zanten ◽  
A. van de sande ◽  
M. P. brocaar
Keyword(s):  
Pure Tone ◽  
Acoustic Emissions ◽  
Shape Similarity ◽  
Pure Tone Audiogram

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

Right-Hemisphere Specialization for Contour Grouping

2014 ◽  
Vol 61 (5) ◽  
pp. 331-339 ◽  
Author(s):  
Gregor Volberg
Keyword(s):  
Right Hemisphere ◽  
Contour Detection ◽  
Global Processing ◽  
Detection Accuracy ◽  
Frequency Spectra ◽  
Visual Hemifield ◽  
Spatial Frequencies ◽  
A Chain ◽  
The Right ◽  
Hemisphere Specialization

Previous studies often revealed a right-hemisphere specialization for processing the global level of compound visual stimuli. Here we explore whether a similar specialization exists for the detection of intersected contours defined by a chain of local elements. Subjects were presented with arrays of randomly oriented Gabor patches that could contain a global path of collinearly arranged elements in the left or in the right visual hemifield. As expected, the detection accuracy was higher for contours presented to the left visual field/right hemisphere. This difference was absent in two control conditions where the smoothness of the contour was decreased. The results demonstrate that the contour detection, often considered to be driven by lateral coactivation in primary visual cortex, relies on higher-level visual representations that differ between the hemispheres. Furthermore, because contour and non-contour stimuli had the same spatial frequency spectra, the results challenge the view that the right-hemisphere advantage in global processing depends on a specialization for processing low spatial frequencies.

Harmonics in frequency spectra: a contribution to differential diagnosis of tremor

2007 ◽  
Vol 34 (S 2) ◽  
Author(s):  
G Ellrichmann ◽  
J Jamrozy ◽  
A Hoffmann ◽  
PH Kraus
Keyword(s):  
Differential Diagnosis ◽  
Frequency Spectra
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