Inaudible High-Frequency Sounds Affect Brain Activity: Hypersonic Effect

2000 ◽  
Vol 83 (6) ◽  
pp. 3548-3558 ◽  
Author(s):  
Tsutomu Oohashi ◽  
Emi Nishina ◽  
Manabu Honda ◽  
Yoshiharu Yonekura ◽  
Yoshitaka Fuwamoto ◽  
...  
Keyword(s):  
High Frequency ◽  
Brain Activity ◽  
Statistical Significance ◽  
Power Spectra ◽  
Low Frequency ◽  
Frequency Component ◽  
Frequency Range ◽  
Frequency Components ◽  
Left Thalamus ◽  
The Brain

Although it is generally accepted that humans cannot perceive sounds in the frequency range above 20 kHz, the question of whether the existence of such “inaudible” high-frequency components may affect the acoustic perception of audible sounds remains unanswered. In this study, we used noninvasive physiological measurements of brain responses to provide evidence that sounds containing high-frequency components (HFCs) above the audible range significantly affect the brain activity of listeners. We used the gamelan music of Bali, which is extremely rich in HFCs with a nonstationary structure, as a natural sound source, dividing it into two components: an audible low-frequency component (LFC) below 22 kHz and an HFC above 22 kHz. Brain electrical activity and regional cerebral blood flow (rCBF) were measured as markers of neuronal activity while subjects were exposed to sounds with various combinations of LFCs and HFCs. None of the subjects recognized the HFC as sound when it was presented alone. Nevertheless, the power spectra of the alpha frequency range of the spontaneous electroencephalogram (alpha-EEG) recorded from the occipital region increased with statistical significance when the subjects were exposed to sound containing both an HFC and an LFC, compared with an otherwise identical sound from which the HFC was removed (i.e., LFC alone). In contrast, compared with the baseline, no enhancement of alpha-EEG was evident when either an HFC or an LFC was presented separately. Positron emission tomography measurements revealed that, when an HFC and an LFC were presented together, the rCBF in the brain stem and the left thalamus increased significantly compared with a sound lacking the HFC above 22 kHz but that was otherwise identical. Simultaneous EEG measurements showed that the power of occipital alpha-EEGs correlated significantly with the rCBF in the left thalamus. Psychological evaluation indicated that the subjects felt the sound containing an HFC to be more pleasant than the same sound lacking an HFC. These results suggest the existence of a previously unrecognized response to complex sound containing particular types of high frequencies above the audible range. We term this phenomenon the “hypersonic effect.”

scholarly journals Stress Recovery Effects of High- and Low-Frequency Amplified Music on Heart Rate Variability

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yoshie Nakajima ◽  
Naofumi Tanaka ◽  
Tatsuya Mima ◽  
Shin-Ichi Izumi
Keyword(s):  
Heart Rate ◽  
White Noise ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Stress Recovery ◽  
Recovery Ratio ◽  
Autonomic Responses ◽  
Frequency Components

Sounds can induce autonomic responses in listeners. However, the modulatory effect of specific frequency components of music is not fully understood. Here, we examined the role of the frequency component of music on autonomic responses. Specifically, we presented music that had been amplified in the high- or low-frequency domains. Twelve healthy women listened to white noise, a stress-inducing noise, and then one of three versions of a piece of music: original, low-, or high-frequency amplified. To measure autonomic response, we calculated the high-frequency normalized unit (HFnu), low-frequency normalized unit, and the LF/HF ratio from the heart rate using electrocardiography. We defined the stress recovery ratio as the value obtained after participants listened to music following scratching noise, normalized by the value obtained after participants listened to white noise after the stress noise, in terms of the HFnu, low-frequency normalized unit, LF/HF ratio, and heart rate. Results indicated that high-frequency amplified music had the highest HFnu of the three versions. The stress recovery ratio of HFnu under the high-frequency amplified stimulus was significantly larger than that under the low-frequency stimulus. Our results suggest that the high-frequency component of music plays a greater role in stress relief than low-frequency components.

Spectral Slope of Vowels Produced by Tracheoesophageal Speakers

1991 ◽  
Vol 34 (2) ◽  
pp. 243-247 ◽  
Author(s):  
Yingyong Qi ◽  
Bernd Weinberg
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Frequency Component ◽  
Least Square ◽  
Group Differences ◽  
Spectral Energy ◽  
Frequency Range ◽  
Spectral Slope ◽  
Matching Procedure ◽  
Autocorrelation Method

Spectra of vowels were analyzed to determine whether differences exist between the spectral slope of vowels produced by tracheoesophageal (TE) speakers and normal speakers and, if so, to quantify such differences. The linear predictive autocorrelation method was used to calculate smoothed spectra and the spectra were normalized with respect to a low frequency component. Comparisons between normalized spectral energy within a selected high frequency range revealed that energy within this frequency range for vowels produced by TE speakers was significantly higher than that produced by normal speakers. A least-square distance matching procedure was used to quantify speaker group differences in the spectral slope of vowels. Average spectra of vowels produced by the normal speakers could be matched to average spectra of vowels produced by the TE speakers by decreasing the spectral slope of their vowels by 2–3 dB/octave.

scholarly journals GEOLOGICAL HETEROGENEITY OF A SEDIMENTARY COVER OF THE PECHORA PLATE ACCORDING TO HYDROMAGNETIC SURVEY

2019 ◽  
Vol 47 (1) ◽  
pp. 161-173
Author(s):  
Yu.V. Brusilovsky ◽  
A.N. Ivanenko
Keyword(s):  
Magnetic Field ◽  
High Frequency ◽  
Sedimentary Cover ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Spectral Structure ◽  
Magnetic Survey ◽  
Frequency Components ◽  
Buried Paleochannels

In August–September, 2018 in the Pechora Sea during the 38th flight of NIS “Academician Nikolay Strakhov” complex geologic-geophysical researches were conducted. Magnetic survey was carried out along with seismic profiling where as the radiator of elastic fluctuations the electrospark Sparker radiator was used. The group of a sea magnetometry was faced by a problem of mapping of the top layer of a sedimentary cover, including allocation of zones of development of thin deposits, buried paleochannels, zones of jointing and geological explosive violations. Hydromagnetic survey and interpretation of the received materials was as a result executed that allowed to estimate spectral structure of the abnormal magnetic field (AMF) and to allocate three frequency components to which there corresponds the deep range of sources of the field. Leaning on the received estimates of depths, and comparing them to the description of wells, also temporary bindings for the allocated deep ranges of sources of magnetic field were defined. High-frequency component, there corresponds the arrangement of sources of AMF in the topmost part of a section. The top edges of sources lie in the range of depths from 35 to 70 m that possibly correspond to deposits of pleystotsenovy age. It is possible that the thin deposits created during the last Valdai freezing can be sources of these high-frequency anomalies. The second deep range is created by sources of AMF the top edges of which are located in the range of depths of 260–510 m that possibly corresponds to stratigrafichesky range from top Yura to the lower chalk. The third, the deep range of bedding of the top edges of sources of AMF allocated by authors is determined by the most low-frequency part of a range and according to authors reflects the late Devonian stage of activization of magmatism.

scholarly journals Nondestructive Tomographic Imaging of Rust with Rapid THz Time-Domain Spectroscopy

2021 ◽  
Vol 11 (22) ◽  
pp. 10594
Author(s):  
Hwan Sik Kim ◽  
Seung Yeob Baik ◽  
Joong Wook Lee ◽  
Jangsun Kim ◽  
Yeong Hwan Ahn
Keyword(s):  
Time Domain ◽  
High Frequency ◽  
Steel Plate ◽  
Low Frequency ◽  
Frequency Component ◽  
Paint Layer ◽  
Time Domain Spectroscopy ◽  
Frequency Components ◽  
Chemical Solutions ◽  
Time Of Flight Imaging

In this study, we developed a rapid nondestructive tool for testing rust spread in a metal covered by a paint layer by using a THz time-domain spectroscopy system at a speed of 100 Hz/pixel. Time-of-flight imaging helps identify rust formation by exclusively obtaining the reflection from the steel below the paint surface. The use of frequency-selective imaging allows us to manipulate the contrast in rust imaging. Higher contrast is generally obtained when monitoring using the higher frequency component. In addition, we monitored the spread of rust in a steel plate under the influence of two different chemical solutions: NaCl and acid. We found that in the early stages, the decrease in THz reflection was governed by the high-frequency components due to the formation of lepidocrocite, whereas the low-frequency component develops as the proportion of hematite increases with time.

scholarly journals A Novel Infrared and Visible Image Information Fusion Method Based on Phase Congruency and Image Entropy

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1135 ◽  
Author(s):  
Xinghua Huang ◽  
Guanqiu Qi ◽  
Hongyan Wei ◽  
Yi Chai ◽  
Jaesung Sim
Keyword(s):  
Image Fusion ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Source Image ◽  
Phase Congruency ◽  
Visible Image ◽  
Image Information ◽  
Frequency Components

In multi-modality image fusion, source image decomposition, such as multi-scale transform (MST), is a necessary step and also widely used. However, when MST is directly used to decompose source images into high- and low-frequency components, the corresponding decomposed components are not precise enough for the following infrared-visible fusion operations. This paper proposes a non-subsampled contourlet transform (NSCT) based decomposition method for image fusion, by which source images are decomposed to obtain corresponding high- and low-frequency sub-bands. Unlike MST, the obtained high-frequency sub-bands have different decomposition layers, and each layer contains different information. In order to obtain a more informative fused high-frequency component, maximum absolute value and pulse coupled neural network (PCNN) fusion rules are applied to different sub-bands of high-frequency components. Activity measures, such as phase congruency (PC), local measure of sharpness change (LSCM), and local signal strength (LSS), are designed to enhance the detailed features of fused low-frequency components. The fused high- and low-frequency components are integrated to form a fused image. The experiment results show that the fused images obtained by the proposed method achieve good performance in clarity, contrast, and image information entropy.

A Raman study of aqueous DMF and DMA solutions at low temperatures

2004 ◽  
Vol 82 (10) ◽  
pp. 1468-1473 ◽  
Author(s):  
K Tomikawa ◽  
H Kanno ◽  
H Kimoto
Keyword(s):  
Aqueous Solution ◽  
High Frequency ◽  
Low Temperatures ◽  
Low Frequency ◽  
Frequency Component ◽  
Solute Concentration ◽  
Area Ratio ◽  
High Frequency Component ◽  
Frequency Components ◽  
Raman Study

Hydrogen bonding in aqueous N,N-dimethylformamide (DMF) and N,N-dimethylacetamide (DMA) solutions was studied by Raman spectroscopy of the OH-stretching spectra of water as functions of solute concentration and temperature (from –50 to 50 °C). The Raman spectra were decomposed successfully into two components (the low- and high-frequency components). The peak area ratio of the low-frequency component to the high-frequency component increases exponentially with decreasing temperature. The frequency of the low-frequency component decreases linearly with lowering temperature down to –50 °C at all solute concentrations (solute mol fraction from 0.3 to 0.7). It is shown that the hydrogen bonds in the clathrate structures around DMA molecules are stronger than those around DMF molecules.Key words: Raman spectrum, DMF, DMA, aqueous solution, low temperature.

Galloping Characteristics of Conductor Accreted with Crescent-Shaped Ice

2012 ◽  
Vol 226-228 ◽  
pp. 158-161 ◽  
Author(s):  
Hui Xue Dang ◽  
Feng Li Yang ◽  
Xin Min Li ◽  
Jing Bo Yang
Keyword(s):  
High Frequency ◽  
Software Package ◽  
Free Stream ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Span Length ◽  
Test Results ◽  
Frequency Components ◽  
Commercial Software Package

Accounting for the disastrous phenomena of ice-accreted conductor galloping, wind tunnel tests of LGJ630/45 conductor accreted with crescent-shaped ice are conducted. Based on the test results, conductor galloping is simulated by employing the PCL language of ANSYS commercial software package and then the influences of span lengths as well as free-stream speeds on galloping characteristics are studied. The results indicate that, conductor galloping consists several different frequency components. With the increase of span length, galloping energy moves from low-frequency component to its high-frequency counterpart, and finally high-frequency component dominates the galloping phenomenon. And with the movement of energy, galloping traces transforms from ellipse to that similar to a butterfly. With the increase of span length, the maximum cable tension first increases, next decreases sharply, and then increases again.

scholarly journals Voiceless Stop Consonant Modelling and Synthesis Framework Based on MISO Dynamic System

2017 ◽  
Vol 42 (3) ◽  
pp. 375-383 ◽  
Author(s):  
Gražina Korvel ◽  
Bożena Kostek
Keyword(s):  
Impulse Response ◽  
High Frequency ◽  
Low Frequency ◽  
Stop Consonant ◽  
Frequency Component ◽  
High Frequency Component ◽  
Frequency Range ◽  
Modelling Framework ◽  
Voiceless Stop ◽  
Consonant Phoneme

AbstractA voiceless stop consonant phoneme modelling and synthesis framework based on a phoneme modelling in low-frequency range and high-frequency range separately is proposed. The phoneme signal is decomposed into the sums of simpler basic components and described as the output of a linear multiple-input and single-output (MISO) system. The impulse response of each channel is a third order quasi-polynomial. Using this framework, the limit between the frequency ranges is determined. A new limit point searching three-step algorithm is given in this paper. Within this framework, the input of the low-frequency component is equal to one, and the impulse response generates the whole component. The high-frequency component appears when the system is excited by semi-periodic impulses. The filter impulse response of this component model is single period and decays after three periods. Application of the proposed modelling framework for the voiceless stop consonant phoneme has shown that the quality of the model is sufficiently good.

FACIAL BIOMETRICS USING NONTENSOR PRODUCT WAVELET AND 2D DISCRIMINANT TECHNIQUES

2009 ◽  
Vol 23 (03) ◽  
pp. 521-543 ◽  
Author(s):  
DAN ZHANG ◽  
XINGE YOU ◽  
PATRICK WANG ◽  
SVETLANA N. YANUSHKEVICH ◽  
YUAN YAN TANG
Keyword(s):  
Tensor Product ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Component ◽  
Feature Representation ◽  
Support Vector ◽  
Facial Features ◽  
Linear Discriminant ◽  
Illumination Changes ◽  
Frequency Components

A new facial biometric scheme is proposed in this paper. Three steps are included. First, a new nontensor product bivariate wavelet is utilized to get different facial frequency components. Then a modified 2D linear discriminant technique (M2DLD) is applied on these frequency components to enhance the discrimination of the facial features. Finally, support vector machine (SVM) is adopted for classification. Compared with the traditional tensor product wavelet, the new nontensor product wavelet can detect more singular facial features in the high-frequency components. Earlier studies show that the high-frequency components are sensitive to facial expression variations and minor occlusions, while the low-frequency component is sensitive to illumination changes. Therefore, there are two advantages of using the new nontensor product wavelet compared with the traditional tensor product one. First, the low-frequency component is more robust to the expression variations and minor occlusions, which indicates that it is more efficient in facial feature representation. Second, the corresponding high-frequency components are more robust to the illumination changes, subsequently it is more powerful for classification as well. The application of the M2DLD on these wavelet frequency components enhances the discrimination of the facial features while reducing the feature vectors dimension a lot. The experimental results on the AR database and the PIE database verified the efficiency of the proposed method.

scholarly journals ABOUT CLASSIFICATION OF ECG SIGNALS BASED ON HIGH-FREQUENCY WAVELET COMPONENTS

2016 ◽  
pp. 63-71
Author(s):  
Paulina Podkur ◽  
Paulina Podkur ◽  
Nikolay Smolentsev ◽  
Nikolay Smolentsev
Keyword(s):  
Myocardial Infarction ◽  
High Frequency ◽  
Wavelet Decomposition ◽  
Low Frequency ◽  
Feature Space ◽  
Frequency Component ◽  
High Frequency Component ◽  
Ecg Signal ◽  
One Dimensional ◽  
Frequency Components

The new design method of the automated classifying system for electrocardiograms recognition (ECG) of healthy and ill patients, based only on high-frequency components of ECG signal with the use of statistical images recognition is offered. Cardiograms of two groups of patients were studied: healthy and those who came through myocardial infarction. The first step of classification method is ECG wavelet decomposition to the 4th level and allocation of four high-frequency ECG components. The choice of the 4th decomposing level is explained by the fact that the first four high-frequency components represent high ECG frequencies from 30 to 350 Hz, and low-frequency component represents the undistorted smoothed ECG signal cleared of high-frequency oscillations. In case of more deep signal expansion the following high-frequency component has frequency spectrum to 30 Hz, and low frequency component is significantly distorted. For each of the first four components of wavelet decomposition there is a number of ECG numerical signs, including energy, entropy and frequency characteristics, 21 signs in total. During the second step reduction of the dimensionality of the feature space by using scatter matrix is made for two chosen ECG groups. It has turned out that the reduced feature space is one-dimensional. Histograms of values of this one-dimensional feature for groups of healthy and ill patients are constructed. The third step is finding of the dividing constant which is able to distinguish both groups of ECG records. For testing 96 ECG records of patients with normal cardiograms and 120 ECG records of the patients who came through myocardial infarction are used. Only three features (3%) of 96 given features values of the first group are referred by the classifier to patients group and only 20 features (< 17%) of 120 given features values of the second patients group are referred by the classifier to ECG group of healthy patients. Considering that for each patient the system determines 12 features by 12 standard assignments, testing results show well classification accuracy.

Sign in / Sign up

Export Citation Format

Share Document