Using Spectral Analysis to Extract Frequency Components from Electroencephalography: Application for Fatigue Countermeasure in Train Drivers

2007 ◽  
Author(s):  
Budi Thomas Jap ◽  
Sara Lal ◽  
Peter Fischer ◽  
Evangelos Bekiaris
Keyword(s):  
Spectral Analysis ◽  
Frequency Components ◽  
Train Drivers

Spectral analysis of heart rate variability of lizard, Gallotia galloti

1988 ◽  
Vol 254 (2) ◽  
pp. R242-R248 ◽  
Author(s):  
J. Gonzalez Gonzalez ◽  
L. De Vera Porcell
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Body Temperature ◽  
Short Term ◽  
Spectral Components ◽  
Frequency Components ◽  
Transient Interactions ◽  
Beat Heart ◽  
Gallotia Galloti

The beat-to-beat heart rate of the lizard, Gallotia galloti, at rest shows short-term oscillations, the frequency of which varies with body temperature. Spectral analysis of the heart rate variability signal shows that, above 20 degrees C, two major frequency components are present: the first component has a mean frequency ranging from 0.032 at 20 degrees C to 0.070 Hz at 35 degrees C and the second from 0.039 at 20 degrees C to 0.10 Hz at 35 degrees C of body temperature. The beat-to-beat heart rate variability does not seem to be correlated with ventilatory activity. The two spectral components could be associated as in mammals with the activity of the control systems that regulate the circulation, especially with the cutaneous vasomotor thermoregulatory and endogenous pressure vasomotor activities. Transient interactions between both components are described.

Continuous, on-line, real-time spectral analysis of SAP signals during cardiopulmonary bypass

1995 ◽  
Vol 268 (6) ◽  
pp. H2329-H2335
Author(s):  
M. W. Yang ◽  
T. B. Kuo ◽  
S. M. Lin ◽  
K. H. Chan ◽  
S. H. Chan
Keyword(s):  
Spectral Analysis ◽  
Cardiopulmonary Bypass ◽  
Blood Vessels ◽  
Real Time ◽  
Low Frequency ◽  
Frequency Component ◽  
Very Low Frequency ◽  
Frequency Components ◽  
On Line ◽  
Very High

We communicated the application of continuous, on-line, real-time power spectral analysis of systemic arterial pressure (SAP) signals during cardiopulmonary bypass when the heart was functionally but reversibly disconnected from the blood vessels. Based on observations from 15 cases of successfully completed coronary artery bypass grafting procedures, we found that the very low (0.00-0.08 Hz), low (0.08-0.15 Hz)-, high (0.15-0.25 Hz)-, and very high (0.80-1.60 Hz) frequency components of SAP signals exhibited differential changes before, during, and after cardiopulmonary bypass. In particular, the very low-frequency component, which purportedly represents the contribution of vasomotor activity to SAP, presented only a mild decrease in power during hypothermic cardioplegia. Interestingly, the total peripheral resistance also manifested only a slight reduction during the same period. On the other hand, the low-, high-, and very high frequency components were essentially eliminated. These results unveiled an active role for the blood vessels in the maintenance of SAP during cardiopulmonary bypass, possibly as a result of a maintained vasomotor tone as reflected by the sustained very low frequency component of the SAP signals.

Auto- and cross-spectral analysis of cardiovascular fluctuations during pentobarbital anesthesia in the rat

1996 ◽  
Vol 270 (2) ◽  
pp. H575-H582 ◽  
Author(s):  
C. C. Yang ◽  
T. B. Kuo ◽  
S. H. Chan
Keyword(s):  
Spectral Analysis ◽  
Intravenous Administration ◽  
Frequency Component ◽  
Systemic Arterial Pressure ◽  
Sprague Dawley ◽  
Sprague Dawley Rats ◽  
Spectral Components ◽  
Autonomic Blockade ◽  
Frequency Components ◽  
Stable Plasma

We applied auto- and cross-spectral analysis of systemic arterial pressure (SAP) and heart rate (HR) signals to quantify the effects of pentobarbital sodium on short-term cardiovascular fluctuations in adult, male Sprague-Dawley rats. Intravenous administration of pentobarbital, delivered as a bolus injection (5, 10, or 20 mg/kg) or continuous infusion (10, 20, or 40 mg.kg-1.h-1), elicited only mild hypotension and tachycardia. This was accompanied by a dose-related depression of the very low (0-0.25 Hz) and low (0.25-0.8 Hz)-frequency components of both SAP and HR signals and high (0.8-2.4 Hz)-frequency component of HR signals. Cross-spectral analysis of SAP and HR signals during intravenous infusion of pentobarbital revealed a maintained coherence in the high-frequency range, together with a gradual and dose-related decrease in magnitude of transfer function and baro-receptor reflex sensitivity. Stable plasma concentration and all hemodynamic parameters were observed during 120 min of infusion at 20 mg.kg-1.h-1. Under this dosing condition, autonomic blockade by phentolamine, propranolol, or atropine still evoked discernible but differential reductions in the SAP and HR spectral components. Our data suggest that continuous intravenous administration of pentobarbital at 20 mg.kg-1.h-1 offers maintained anesthesia while preserving the capacity of cardiovascular regulation.

Coarse-graining spectral analysis: new method for studying heart rate variability

1991 ◽  
Vol 71 (3) ◽  
pp. 1143-1150 ◽  
Author(s):  
Y. Yamamoto ◽  
R. L. Hughson
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
High Frequency ◽  
Low Frequency ◽  
Scale Invariant ◽  
Very Low Frequency ◽  
Frequency Components ◽  
Harmonic Components

Heart rate variability (HRV) spectra are typically analyzed for the components related to low- (less than 0.15 Hz) and high- (greater than 0.15 Hz) frequency variations. However, there are very-low-frequency components with periods up to hours in HRV signals, which might smear short-term spectra. We developed a method of spectral analysis suitable for selectively extracting very-low-frequency components, leaving intact the low- and high-frequency components of interest in HRV spectral analysis. Computer simulations showed that those low-frequency components were well characterized by fractional Brownian motions (FBMs). If the scale invariant, or self-similar, property of FBMs is considered a new time series (x′) was constructed by sampling only every other point (course graining) of the original time series (x). Evaluation of the cross-power spectra between these two (Sxx′) showed that the power of the FBM components was preserved, whereas that of the harmonic components vanished. Subtraction of magnitude of Sxx from the autopower spectra of the original sequence emphasized only the harmonic components. Application of this method to HRV spectral analyses indicated that it might enable one to observe more clearly the low- and high-frequency components characteristic of autonomic control of heart rate.

Power spectral analysis for autonomic influences in heart rate and blood pressure variability in fetal lambs

1996 ◽  
Vol 271 (4) ◽  
pp. H1333-H1339 ◽  
Author(s):  
Y. Kimura ◽  
K. Okamura ◽  
T. Watanabe ◽  
J. Murotsuki ◽  
T. Suzuki ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Spectral Analysis ◽  
Power Spectrum ◽  
Blood Pressure Variability ◽  
Power Spectral Analysis ◽  
Sympathetic Blockade ◽  
Arterial Blood ◽  
Power Spectral ◽  
Frequency Components

Variability of R-R intervals and arterial blood pressure signals in chronically instrumented fetal lambs was analyzed by power spectral analysis based on an assumption of maximum entropy. There were four consistent components, very low (VL, 0.01-0.025 cycle/beat), low (L, 0.025-0.125 cycle/beat), middle (M, 0.125-0.2 cycle/beat), and high (H, 0.2-0.5 cycle/beat), in the normal heart rate variability and blood pressure spectra. Integrated peaks in the power spectrum were compared before and after the administration of sympathetic and parasympathetic blockades. beta-Sympathetic blockade reduced the spectral power in the VL and L frequency components. alpha-Sympathetic blockade reduced only the M frequency component in the spectrum of R-R interval variability. Parasympathetic blockade reduced the H and L frequency components in the R-R interval variability spectrum but increased these components in the systolic blood pressure variability spectrum. The results clearly demonstrate the association between fetal autonomic activity and change of power spectrum of heart rate and blood pressure variability.

An accurate recording system and its use in breath sounds spectral analysis

1983 ◽  
Vol 55 (4) ◽  
pp. 1120-1127 ◽  
Author(s):  
G. Charbonneau ◽  
J. L. Racineux ◽  
M. Sudraud ◽  
E. Tuchais
Keyword(s):  
Spectral Analysis ◽  
Flow Rate ◽  
High Frequency ◽  
Recording System ◽  
Spectral Features ◽  
Breath Sounds ◽  
Frequency Components ◽  
Set Up ◽  
Different Characteristics ◽  
Sound Features

An accurate recording system was set up and used for analyzing normal and asthmatic breath-sound features. Breath sounds are recorded at the trachea simultaneously with the airflow signal at 0.5- and 1-1/s levels. The study was carried out in the frequency domain using a fast-fourier transform (FFT). FFTs are taken on 1,024-sample blocks (one block = 200 ms) over a duration of about 20 s. Different characteristics of the spectra are calculated in the range 60-1,260 Hz for 11 normal and 10 asthmatic subjects. This allows the computation of an index that discriminates (P less than 0.0005) asthma cases from normal cases. Spectral features strongly depend on the flow rate both for normal and asthmatic subjects. Increasing the flow rate raises the high-frequency components of the spectra.

Numerical analysis and experimental verification of broadband tristable energy harvesters

2018 ◽  
Vol 85 (9) ◽  
pp. 521-532 ◽  
Author(s):  
Shengxi Zhou ◽  
Junyi Cao ◽  
Grzegorz Litak ◽  
Jing Lin
Keyword(s):  
Spectral Analysis ◽  
Bifurcation Diagram ◽  
Chaotic Oscillation ◽  
Excitation Amplitude ◽  
Response Mechanism ◽  
Third Harmonic ◽  
Energy Harvesters ◽  
Triply Periodic ◽  
Period Oscillation ◽  
Frequency Components

Abstract This paper analyzes the dynamic characteristics of broadband tristable energy harvesters to reveal their response mechanism via a bifurcation diagram, the corresponding frequency spectral analysis and the phase portrait topology. The bifurcation diagram of response voltages shows that tristable energy harvesters orderly undergoes singly periodic intrawell oscillation, singly periodic interwell oscillation, triply periodic interwell oscillation, singly periodic interwell oscillation, double-periodic interwell oscillation, chaotic oscillation, singly periodic interwell oscillation, multi-period oscillation, and finally enters into chaotic oscillation range, as the increase of the excitation amplitude. The frequency spectral analysis demonstrates that sub-harmonics and super-harmonics numerically and experimentally exist in the response voltages of tristable energy harvesters. In addition, it is found that both the first harmonic and the third harmonic are main frequency components in the response voltages.

scholarly journals Even slight movements disturb analysis of cardiovascular dynamics

1999 ◽  
Vol 277 (1) ◽  
pp. H261-H267 ◽  
Author(s):  
Jacques-Olivier Fortrat ◽  
Cédric Formet ◽  
Jean Frutoso ◽  
Claude Gharib
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Low Frequency ◽  
Coarse Graining ◽  
Spectral Exponent ◽  
Spontaneous Movements ◽  
Frequency Components ◽  
Fractal Noise

We hypothesized that spontaneous movements (postural adjustments and ideomotion) disturb analysis of heart rate and blood pressure variability and could explain the discrepancy between studies. We measured R-R intervals and systolic blood pressure in nine healthy sitting subjects during three protocols: 1) no movement allowed, 2) movements allowed but not standing, 3) movements and standing allowed. Heart rate and blood pressure were not altered by movements. Movements with or without standing produced a twofold or greater increase of the overall variability of R-R intervals and of the low-frequency components of spectral analysis of heart rate variability. The spectral exponent β of heart rate variability (1.123 at rest) was changed by movements (1.364), and the percentage of fractal noise (79% at rest) was increased by standing (91%, coarse-graining spectral analysis). Spontaneous movements could induce a plateau in the correlation dimensions of heart rate variability, but they changed its nonlinear predictability. We suggest that future studies on short-term cardiovascular variability should control spontaneous movements.

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