Backscattering Spectrogram
Backscattering Spectrogram - Related Videos
04:13
Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
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Cited by 14 •
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This protocol provides an open source, compiled MATLAB program that generates multitaper spectrograms for electroencephalographic data.
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Voice disorders are debilitating in aging and Parkinson disease. The ultrasonic vocalizations of rats, also affected by these conditions, can be used to study these voice disorders, their neural substrates, and the nature of functional recovery with behavioral intervention.
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Comprehensive Characterization of Extended Defects in Semiconductor Materials by a Scanning Electron Microscope
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Cited by 4 •
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The optical, electrical, and structural properties of dislocations and of grain boundaries in semiconductor materials can be determined by experiments performed in a scanning electron microscope. Electron microscopy has been used to investigate cathodoluminescence, electron beam induced current, and diffraction of backscattered electrons.
10:25
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Cited by 1 •
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We present here a protocol to construct and validate models for nondestructive prediction of total sugar, total organic acid, and total anthocyanin content in individual blueberries by near-infrared spectroscopy.
05:49
Laser Micromachining for Polymer Surface Topography Design
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2025
A method for imposing surface topography of light-absorbing composite polymer materials, particularly magnetoactive elastomers (MAEs), by using laser micromachining is presented. This method enables large flexibility in topographical designs and rapid prototyping. An example of structuring MAE surfaces, characterization, and their response to the external magnetic field is demonstrated.
FAQs
Time-frequency analysis separates the returned signal into frequency components while preserving their progression over time. This allows researchers to examine when particular signal patterns occur, rather than treating the response as one combined waveform. The resulting map can expose temporal changes associated with tissue interfaces, motion, or composition that may be difficult to distinguish in an undivided signal.
Intensity variations indicate differences in the strength of signal energy returned from tissue at particular times and frequencies. Those differences reflect how biological structures modify the incident signal through their scattering properties. Comparing stronger and weaker regions can therefore help researchers identify changes in interfaces, motion, or tissue composition and relate them to measurable biological structure.
A single waveform presents the backscattered response as a time-domain signal, whereas the spectrogram organizes its energy across both time and frequency. This additional organization makes subtle signal patterns easier to compare. For biomedical research, the comparison can clarify whether an observed change reflects altered timing, frequency content, or overall signal intensity.
The process begins by recording the signal returned after waves interact with tissue. The recorded backscattered response is then resolved into frequency components over time, producing a time-frequency map of signal energy. Researchers can inspect changes in intensity across that map and compare the resulting patterns to differences in scattering properties, interfaces, motion, or tissue composition.
Medical researchers may use the representation for tissue characterization, imaging, and monitoring. Its time-frequency patterns provide a way to examine how biological structures affect a returned signal and how those effects change over time. This supports comparisons among tissue conditions or observations made during monitoring, while contributing to noninvasive assessment and quantitative biomedical research.
It can provide measurable patterns linking returned signal energy with tissue-related features. Researchers may evaluate intensity changes across time and frequency to study differences in scattering properties, interfaces, motion, or composition. Interpreting these patterns helps connect signal behavior with physiological structure and change, which is important for tissue characterization and monitoring applications.