"Smooth" Rhythms as Probes of Entrainment

1993 ◽  
Vol 10 (4) ◽  
pp. 503-508 ◽  
Author(s):  
Robert O. Gjerdingen
Keyword(s):  
Frequency Domain ◽  
Amplitude Modulation ◽  
Acoustic Signal ◽  
Low Frequency ◽  
Digital Filtering ◽  
Acoustic Signals ◽  
Frequency Range ◽  
Carrier Wave ◽  
The Brain

If one hypothesizes rhythmic perception as a process employing oscillatory circuits in the brain that entrain to low-frequency periodicities in the neural firings evoked by an acoustic signal, then among the conceptually purest probes of those oscillatory circuits would be acoustic signals with only simple sinusoidal periodicities in the appropriate frequency range (perhaps from 0.3 Hz to 20 Hz). Such signals can be produced by the low- frequency amplitude modulation of an audible carrier wave by one or more sinusoids. The resulting rhythms are "smooth" in that their amplitude envelopes are smoothly varying with no obvious points of onset or offset. Because preliminary experiments with smooth rhythms have produced some unexpected results, and because smooth rhythms can be precisely controlled and varied (including, for example, the digital filtering of their Fourier components in the frequency domain), they are proposed as versatile stimuli for studies in rhythmic perception.

scholarly journals Low Frequency Noise Remove from EEG Signal

2020 ◽  
Vol 9 (1) ◽  
pp. 1510-1513
Keyword(s):  
Human Brain ◽  
Random Noise ◽  
Low Frequency ◽  
Frequency Noise ◽  
Eeg Signal ◽  
Low Frequency Noise ◽  
Frequency Range ◽  
Average Value ◽  
Different Types ◽  
The Brain

The electrical activity of the brain recorded by EEG which used to detect different types of diseases and disorders of the human brain. There is contained a large amount of random noise present during EEG recording, such as artifacts and baseline changes. These noises affect the low -frequency range of the EEG signal. These artifacts hiding some valuable information during analyzing of the EEG signal. In this paper we used the FIR filter for removing low -frequency noise(<1Hz) from the EEG signal. The performance is measured by calculating the SNR and the RMSE. We obtained RMSE average value from the test is 0.08 and the SNR value at frequency(<1Hz) is 0.0190.

scholarly journals Impact of mild orthostatic stress on aortic-cerebral hemodynamic transmission: insight from the frequency domain

2017 ◽  
Vol 312 (5) ◽  
pp. H1076-H1084 ◽  
Author(s):  
Jun Sugawara ◽  
Tsubasa Tomoto ◽  
Tomoko Imai ◽  
Seiji Maeda ◽  
Shigehiko Ogoh
Keyword(s):  
Transfer Function ◽  
Frequency Domain ◽  
Systemic Vascular Resistance ◽  
Vascular Resistance ◽  
Low Frequency ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Slow Oscillations ◽  
Transfer Function Gain ◽  
The Brain

High cerebral pressure and flow fluctuations could be a risk for future cerebrovascular disease. This study aims to determine whether acute systemic vasoconstriction affects the dynamic pulsatile hemodynamic transmission from the aorta to the brain. We applied a stepwise lower body negative pressure (LBNP) (−10, −20, and −30 mmHg) in 15 young men to induce systemic vasoconstriction. To elucidate the dynamic relationship between the changes in aortic pressure (AoP; estimated from the radial arterial pressure waveforms) and the cerebral blood flow velocity (CBFV) at the middle cerebral artery (via a transcranial Doppler), frequency-domain analysis characterized the beat-to-beat slow oscillation (0.02–0.30 Hz) and the intra-beat rapid change (0.78–9.69 Hz). The systemic vascular resistance gradually and significantly increased throughout the LBNP protocol. In the low-frequency range (LF: 0.07–0.20 Hz) of a slow oscillation, the normalized transfer function gain of the steady-state component (between mean AoP and mean CBFV) remained unchanged, whereas that of the pulsatile component (between pulsatile AoP and pulsatile CBFV) was significantly augmented during −20 and −30 mmHg of LBNP (+28.8% and +32.4% vs. baseline). Furthermore, the relative change in the normalized transfer function gain of the pulsatile component at the LF range correlated with the corresponding change in systemic vascular resistance ( r = 0.41, P = 0.005). Regarding the intra-beat analysis, the normalized transfer function gain from AoP to CBFV was not significantly affected by the LBNP stimulation ( P = 0.77). Our findings suggest that systemic vasoconstriction deteriorates the dampening effect on the pulsatile hemodynamics toward the brain, particularly in slow oscillations (e.g., 0.07–0.20 Hz). NEW & NOTEWORTHY We characterized the pulsatile hemodynamic transmission from the heart to the brain by frequency-domain analysis. The low-frequency transmission was augmented with a mild LBNP stimulation partly due to the elevated systemic vascular resistance. A systemic vasoconstriction deteriorates the dampening effect on slow oscillations of pulsatile hemodynamics toward the brain.

Seismoacoustic analysis of underground explosions using the Rayleigh integral

2020 ◽  
Vol 223 (2) ◽  
pp. 1069-1085 ◽  
Author(s):  
Philip Blom ◽  
Alex Iezzi ◽  
Garrett Euler
Keyword(s):  
Ground Motion ◽  
Acoustic Signal ◽  
Low Frequency ◽  
Free Fall ◽  
Acoustic Signals ◽  
Frequency Component ◽  
Underground Explosion ◽  
Ground Zero ◽  
Surface Motion ◽  
Explosion Monitoring

SUMMARY A coupled seismoacoustic model is developed for the analysis of acoustic signals produced by underground explosive events with an aim to develop a means of improving estimated depth and yield for explosion monitoring. A ground spall model is used to predict surface motion characteristics produced by an underground explosion and the Rayleigh integral is applied to relate the surface motion to the acoustic signal some distance from surface ground zero. The low-frequency component of the ground motion associated with the prolonged free fall of lofted material during spall is found to dominate the acoustic signal propagating away from surface ground zero at shallow angles. The model is applied to observed ground motion and acoustic signals recorded during the Source Physics Experiment (SPE) with promising results. In addition to accurately predicting characteristics of the observed acoustic signals from several of the SPE events, the model provides a means of explaining the lack of signals observed during several events in the SPE due to the directionality of the higher frequency acoustic signals associated with the uplift and closure components as well as the lack of a spatially localized, longer duration dwell.

scholarly journals IDENTIFICATION OF ACOUSTIC SIGNATURES FOR VEHICLES VIA REDUCTION OF DIMENSIONALITY

2004 ◽  
Vol 02 (01) ◽  
pp. 1-22 ◽  
Author(s):  
AMIR AVERBUCH ◽  
EYAL HULATA ◽  
VALERY ZHELUDEV ◽  
INNA KOZLOV
Keyword(s):  
Frequency Domain ◽  
Acoustic Signal ◽  
Acoustic Signals ◽  
False Alarms ◽  
Reduction Of Dimensionality ◽  
Acoustic Signatures ◽  
Acoustic Signature ◽  
Moving Vehicles ◽  
Wide Range

In this paper we propose a robust algorithm that solves two related problems: (1) Classification of acoustic signals emitted by different moving vehicles. The recorded signals have to be identified to which pre-existing group they belong to independently of the recording surrounding conditions. (2) Detection of the presence of a vehicle in a certain class via analysis of its acoustic signature against the existing database of recorded and processed acoustic signals. To achieve this detection with minimal false alarms we construct the acoustic signature of a certain vehicle using the distribution of the energies among blocks which consist of coefficients of multiscale local cosine transform (LCT) applied in the frequency domain of the acoustic signal. The proposed algorithm is robust even under severe noise and diverse rough surrounding conditions. This is a generic technology, which has many algorithmic variations, can be used to solve wide range of classification and detection problems which are based on a unique derivation of signatures.

scholarly journals Acute Effect of Kapalbhati Yoga on Cardiac Autonomic Control Using Heart Rate Variability Analysis in Healthy Male Individuals

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Rajeev Gupta
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
High Frequency ◽  
Low Frequency ◽  
Acute Effect ◽  
Sympathetic Activation ◽  
Frequency Range ◽  
Healthy Male ◽  
Band Power

Kapalbhati is well known for improving cardiovascular health. But there are some reports of heart attacks while practising kapalbhati. We hypothesize that ill-effect of kapalbhati could be because of autonomic dysfunction to heart. In the present study, we aim to understand the acute effect of kapalbhati yoga on heart rate dynamics using heart rate variability (HRV) analysis. Resting heart rate (HR) varies widely in different individuals and during various physiological stresses, particularly, exercise it can go up to three-fold. These changes in heart rate are known as heart rate variability (HRV). Variability in heart rate reflects the control of autonomic system on the heart and which can be determined during brief periods of electrocardiographic (ECG) monitoring. HRV measures the effect of any physical exercise on the heart rate using time- and frequency-domain methods. Frequency-domain method involves power spectral analyses of the beat-to-beat intervals (R-R intervals) variability data. When total power vs. frequency, fast fourier transform analysis of R-R intervals data is done, it shows three well-defined peaks/rhythms in every individual, which contain different physiological information. Thus, the total spectral power of R-R intervals data can be divided into three components or bands viz., the very low frequency (VLF) band, the low-frequency (LF) band and the high frequency (HF) band. VLF represent very long time-period physiological phenomenon like thermoregulation, circadian rhythms etc. and thus are not seen in short-term recordings like in this work. LF band power represents long period physiological rhythms in the frequency range of 0.05- 0.15 Hz and LF band power increases as a consequence of sympathetic activation. HF band represent physiological rhythms in the frequency range of 0.15-0.5 Hz and they are synchronous with the respiration rate, and arise due to the intrathoracic pressure changes and mechanical vibrations caused by the breathing activity. In this work, twenty healthy male volunteers were trained in kapalbhati yoga and their ECG waveforms (2 min.) were obtained while doing kapalbhati (breathing at 1 Hz frequency for 2 min.) and were compared with the baseline (just 2 min. before the start) and post-kapalbhati (immediately 2 min. after completing the practice) HRV data. Our results showed a significant decrease in the time-domain measures i.e., NN50, pNN50 and the mean heart rate interval during-kapalbhati when compared statistically to the respective before practice or “pre”-kapalbhati (p < 0.05, student’s paired t-test) values. Frequency-domain indices showed that during-kapalbhati there is a significant increase (~48%) in the LF band power which suggests sympathetic activation and a significant increase (~88%) in the low frequency to the high frequency power ratio (LF/HF ratio) which indicates sympathetic system predominance. A significant decrease (~63%) in the HF component was also noted during-kapalbhati as compared to the “pre-kapalbhati” values which shows decrease in parasympathetic tone. Thus, these results suggest that during-kapalbhati there is drastic increase of sympathetic tone whereas parasympathetic activity is reduced. We propose these changes in autonomic system control on heart are responsible for the myocardial ischemic attacks induced during kapalbhati in some individuals.

Low Frequency High Level Noise Impulses near Weapons and Explosions

1988 ◽  
Vol 7 (2) ◽  
pp. 42-49 ◽  
Author(s):  
Rauno Paakkonen
Keyword(s):  
Frequency Domain ◽  
Impulse Noise ◽  
Energy Content ◽  
Low Frequency ◽  
Frequency Range ◽  
Frequency Peak ◽  
High Level ◽  
Peak Value

Analyses with a waveform analyser were made of the time and frequency domain of impulse noise from both military guns, e.g. rifles, cannons, bazookas and mortars, and explosions. For heavy weapons the most prominent energy content was found to be in the frequency range below 100 Hz. The frequency peak was generally less than 50 Hz. The significance for the A-weighting of noise impulses from weapons is discussed, as well as the different impulse parameters, e.g. peak value, impulse energy and A-duration.

Study on the Stepping Identification Arithmetic for Broadband EMP Test System

2013 ◽  
Vol 475-476 ◽  
pp. 643-647
Author(s):  
Ting An ◽  
Xue Hua Jiang
Keyword(s):  
Frequency Domain ◽  
High Frequency ◽  
Low Frequency ◽  
Test System ◽  
Practical Application ◽  
Frequency Range ◽  
Frequency Model ◽  
Building Model ◽  
Poles And Zeros ◽  
Identification Model

In order to overcome the limitation of common methods in modeling test system of broadband electromagnetic pulse (EMP), the paper provided a stepping identification arithmetic to solve the problem of building model in whole frequency range. It obtained low-frequency model and high-frequency model respectively in low-frequency domain and high-frequency domain by identification using import signal and output signal measured by test, it obtained the identification model of the test system by connecting the low-frequency model and high-frequency model, the model was simplified by offsetting adjacent poles and zeros. The results of simulation and test show that the papers method can reflect the dynamic characteristic of the system in whole frequency range, and it is feasible in practical application.

LOW FREQUENCY MODES PROBED BY TIME-DOMAIN OPTICAL KERR EFFECT SPECTROSCOPY

1996 ◽  
Vol 10 (11) ◽  
pp. 1229-1272 ◽  
Author(s):  
S. KINOSHITA ◽  
Y. KAI ◽  
T. ARIYOSHI ◽  
Y. SHIMADA
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Kerr Effect ◽  
Low Frequency ◽  
Great Accuracy ◽  
Wide Frequency Range ◽  
Optical Kerr Effect ◽  
Spectroscopic Techniques ◽  
Frequency Range ◽  
Debye Relaxation

The principle and application of ultrafast optical Kerr effect (OKE) spectroscopy have been reviewed. This spectroscopy is shown to be very useful to investigate low frequency modes in disordered materials and the obtained data are directly comparable with frequency-domain light scattering spectroscopy. Experimental study to show the consistency between the time- and frequency-domain spectroscopy has been performed for liquid nitrobenzene and the excellent agreement is attained over three orders of magnitude in frequency range. It is also shown that the result obtained by the OKE measurement is consistent with that obtained by four wave mixing spectroscopy. Combination of these spectroscopic techniques is particularly suited for the investigation of low frequency modes because a wide frequency range is covered with great accuracy. Several remarks concerning the OKE spectroscopy are presented such as the breakdown of Debye relaxation model and various interference effects which may distort the time-domain data.

Infra-sound cancellation and mitigation in wind turbines

2018 ◽  
Vol 7 (1) ◽  
pp. 73-81
Author(s):  
Albert Boretti ◽  
Andrew Ordys ◽  
Sarim Al Zubaidy
Keyword(s):  
Hearing Loss ◽  
Amplitude Modulation ◽  
Pressure Wave ◽  
Endolymphatic Hydrops ◽  
Low Frequency ◽  
Frequency Noise ◽  
Frequency Range ◽  
Large Pressure ◽  
Active Cancellation ◽  
Sound Cancellation

Abstract The infra-sound spectra recorded inside homes located even several kilometres far from wind turbine installations is characterized by large pressure fluctuation in the low frequency range. There is a significant body of literature suggesting inaudible sounds at low frequency are sensed by humans and affect the wellbeing through different mechanisms. These mechanisms include amplitude modulation of heard sounds, stimulating subconscious pathways, causing endolymphatic hydrops, and possibly potentiating noise-induced hearing loss. We suggest the study of infra-sound active cancellation and mitigation to address the low frequency noise issues. Loudspeakers generate pressure wave components of same amplitude and frequency but opposite phase of the recorded infra sound. They also produce pressure wave components within the audible range reducing the perception of the infra-sound to minimize the sensing of the residual infra sound.

scholarly journals Binaural Heterophasic Superdirective Beamforming

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 74
Author(s):  
Yuzhu Wang ◽  
Jingdong Chen ◽  
Jacob Benesty ◽  
Jilu Jin ◽  
Gongping Huang
Keyword(s):  
White Noise ◽  
Auditory System ◽  
Sound Source ◽  
Acoustic Signal ◽  
Random Phase ◽  
Acoustic Signals ◽  
Acoustic Arrays ◽  
Noise Amplification ◽  
The Brain ◽  
Diffuse Noise

The superdirective beamformer, while attractive for processing broadband acoustic signals, often suffers from the problem of white noise amplification. So, its application requires well-designed acoustic arrays with sensors of extremely low self-noise level, which is difficult if not impossible to attain. In this paper, a new binaural superdirective beamformer is proposed, which is divided into two sub-beamformers. Based on studies and facts in psychoacoustics, these two filters are designed in such a way that they are orthogonal to each other to make the white noise components in the binaural beamforming outputs incoherent while maximizing the output interaural coherence of the diffuse noise, which is important for the brain to localize the sound source of interest. As a result, the signal of interest in the binaural superdirective beamformer’s outputs is in phase but the white noise components in the outputs are random phase, so the human auditory system can better separate the acoustic signal of interest from white noise by listening to the outputs of the proposed approach. Experimental results show that the derived binaural superdirective beamformer is superior to its conventional monaural counterpart.

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