Spectral methods of heart rate variability analysis during dynamic exercise

The present study aims to establish normal limits of short–term Heart Rate Variability (HRV) indices with the two popular spectral domain methods of Fast Fourier Transform (FFT) and Autoregressive (AR) model in three psychosomatically important age groups of healthy male subjects. The three considered age groups are 18–30 years, 30–45 years and 45–60 years and HRV decreases in the higher age groups when evaluated with both the FFT and AR models. Vagal control becomes weak with the ageing process. However, the corresponding HRV indices computed with both the FFT and AR models differ quantitatively, which may be due to methodological differences. The FFT–based technique evaluates HRV indices on the actual RR interval series length and hence, the HRV indices using this technique are considered to be highly accurate, where as the AR model works on the basis of linear prediction. This study may help towards optimisation of AR models such that the HRV indices calculated with both FFT and AR models are nearly the same.

In passive narrow-band or broadband target detection sonars, line arrays are used to enhance performance. In large towed arrays, wave-number-frequency (k-ω) data analysis methods have been used on an experimental basis to detect and identify the presence of noise generators. The noise sources are composed of acoustically radiating sources located in the ocean, vibrational energy within the array, and pressure disturbances along the array. In this paper, a hybrid autoregressive (AR) technique is presented that will generate k-ω solutions having better spatial resolution than is currently possible with methods that make use of a two-dimensional fast Fourier transform (FFT). The hybrid AR method is implemented by applying a one-dimensional FFT on the sampled time series data and using this result to obtain an averaged array cross-spectral density matrix. The AR method is now applied to the spatial cross spectral density matrix to obtain a wave-number-frequency spectrum. For the hybrid AR method, equations are presented for calculating the spatial wave-number resolution as a function of signal-to-noise ratio (SNR), array size, and time-bandwidth product (T-BW). The equations for resolution and array gain are useful for determining when to apply the hybrid AR method. In addition to the hybrid AR development, a modification of the FFT–FFT method is introduced that provides efficient and rapid computation of a standard wave-number-frequency spectrum. Comparisons for various SNR, AR order, and T-BW conditions using computer simulated, and actual at-sea data are made between the k-ω solutions obtained using this modified FFT method and our proposed hybrid AR technique.

Spectral decomposition of heart rate variability using generalized harmonic analysis

The effects of steady state exercise on the power spectrum of heart rate variability were studied in 19 healthy subjects. Continuous ECG signals were recorded during 1) 15 min of rest in the supine state, 2) 10 min of standing, 3) 10 min of steady state exercise at 50% of maximum predicted power output on a cycle ergometer, and 4) 15 min of post-exercise recovery in the supine state. Autoregressive modeling was used to determine the power spectrum of heart rate variability. While orthostatic stress produced a significant 51% increase in the ratio of low to high frequency peak spectral power, steady state exercise caused a significant suppression of both low and high frequency components. The low frequency peak power rose to significantly high levels throughout 15 min of the post-exercise recovery period. There was a significant leftward shift in the frequency of the low frequency peak with exercise and a rightward shift during the recovery supine state. These results suggest that neuroregulatory control of heart rate plays a major role in adaptive responses to orthostatic stress and post-exercise recovery, while humoral factors are probably more important in maintaining heart rate during steady state exercise.

The origin of very low frequency (VLF) oscillations in the power spectra of heart rate variability (HRV) is controversial with possible mechanisms involving thermoregulation and/or renin-angiotensin-aldosterone system. Recently, a major contribution from vagal influences has been suggested. The present study investigated the behaviour of VLF (0.004–0.040 Hz) components of HRV power spectra in a group of healthy male volunteers during their exposure to (1) dry, supine, immersion in thermo-neutral water for 6 h (n = 7) and (2) non-hypoxic hypobaria (breathing 40–60% oxygen at 15 000′ simulated in a decompression chamber) for 5 h (n = 15). The two manoeuvres are established to increase vagal outflow. During both the manoeuvres, all the frequency domain indices of HRV exhibited a significant increase. Increase in HRV was much more than that in the R-R interval. At 6 h of immersion, the R-R interval increased by ∼15% but the total power increased ∼fourfold. Similarly, at 5 h of exposure to hypobaria, total power increased ∼twofold with a very modest increase in an R-R of ∼9%. Increase in spectral power was appreciable even after normalization with mean R-R2. Increase in VLF during immersion was more than reported during enalaprilat blockade of angiotensin convertase enzyme. Plasma renin activity did not vary during hypobaria. There was a significant increase in pNN50, an established marker of cardiac vagal activity. Centre frequencies of the spectra and slope (β) of the relation between log(PSD) and log(frequency) did not change. Results were supportive of the notion that the parasympathetic system is pre-potent to influence slower (than respiratory) frequency components in HRV spectrum. Additionally, such an effect was without a change in the time constant of effector responses or pacemaker frequencies of VLF and LF periodicities and HRV was not a simple linear surrogate for cardiac vagal effects. An invariance of spectral exponent (β) ruled out contamination of VLF and LF spectra from fractal power as an alternate explanation.

To evaluate the effects of record length selection on the accuracy of spectral estimates of heart rate variability (HRV), a simulation study was carried out using a set of 58 signals obtained by autoregressive (AR) fitting a representative sample of real HRV signals. Four record lengths of 180, 300, 420, and 540 s were considered. Spectral estimation was performed by both the Blackman-Tukey (B-T) and AR methods. Accuracy was assessed for: 1) point spectral estimates, by computing the normalized averaged bias (NAB) and variance (NAV); and 2) the most commonly used spectral parameters [total power (TP) and the powers in the bands: very low frequency (VLF) (0 divided by 0.04 Hz), low frequency (LF) (0.04 divided by 0.15 Hz), and high frequency (HF) (0.15 divided by 0.45 Hz)], by computing the normalized bias (NB) and variance (NV). The results are: whatever the record length considered, the 90th percentiles (90P) of the NAB were < 10%, whereas those of the NB were < 9% for TP, LF, and HF powers, and < 14% for the VLF power, in both methods. The NAV was proportional to the reciprocal of record length, showing high 90P values for the shortest record length (26.4% for B-T and 44.2% for AR). The NV showed the same trend but 90P values were much lower (< 8% for TP, LF, and HF powers and < 19% for VLF power, in both methods). In the final part of the paper a procedure for the computation of approximate upper bounds of the relative absolute error of spectral measures at each record length, based on the knowledge of the NB and NV, is presented.

Dominant frequency (DF) of electrophysiological data is an effective approach to estimate the activation rate during Atrial Fibrillation (AF) and it is important to understand the pathophysiology of AF and to help select candidate sites for ablation. Frequency analysis is used to find and track DF. It is important to minimize the catheter insertion time in the atria as it contributes to the risk for the patients during this procedure, so DF estimation needs to be obtained as quickly as possible. A comparison of computation tim- es taken for spectrum estimation analysis is presented in this paper. Fast Fourier Transform (FFT), Blackman-Tukey (BT), Autoregressive (AR) and Multiple Signal Classification (MUSIC) methods are used to obtain the frequency spectrum of the signals. The time to produce DF was measured for each method. The method which takes the shortest time for analysis is selected for real time application purpose.

Background. Cardiovascular system recovery after physical activity with explosive exercises is essential for cardiovascular pathology prevention. The efficiency of short-term biofeedback training (BFB training) in such conditions in adolescents have not been studied earlier. Objective. Our aim was to study the effect of BFB training on cardiovascular rehabilitation after speed and power training in adolescents according to general heart rate variability (HRV) spectrum total power parameter. Methods. The research has included healthy eighth-grade students (14–15 years old boys) from regular school. Inclusion in experimental and control groups was regulated by researches. Such indicators as total power (TP) of HRV spectrum, tension index (TI), systolic and diastolic arterial blood pressure (ABP), heart rate (HR) were registered initially, after three standing long jumps with double take-off and after recovery. All members of experimental group performed BFB training in order to increase TP (3 min) during recovery period. Members of control group were resting. Results. Initially all members of experimental (n = 17) and control (n = 10) groups were compared on age, height, weight and TP, TI, ABP and HR indicators. The TP level in boys of experimental group was higher than in control group during recovery period after BFB training: 3.22 (1.96; 6.13) against 1.36 (1.15; 1.84) X 1000 ms2 respectively (р = 0.041). There were no differences in TI, ABP and HR levels between two groups during recovery period. Conclusion. Implementation of short-term BFB training according to general HRV spectrum total power parameter in 14–15 years old boys after speed and power training perpetuates vagal impact on heart rate during recovery period.

Context: Cardiac autonomic dysfunction may develop in patients with polycystic ovary syndrome (PCOS). Purpose: evaluation of cardiovascular autonomic functional modulation by using HRV in females with PCOS. Methodology: Thirty patients with PCOS and 30 healthy female volunteers who were matched for age and body mass index (BMI) were enrolled in the study. Frequency domain power spectral analysis of heart rate variability (HRV) did using non- parametric method of Fast Fourier Transform, using Kubios HRV analysis software. Results: compared to controls females with PCOS demonstrated a significant reduction in Total power of HRV & High frequency (HF) during rest compared to controls (p=0.016) (p=0.00) & significant increase in Low frequency (LF) (p=0.0134) and LF/HF ratio. (p=0.000). Conclusion: we conclude that females with PCOS have altered cardiac autonomic modulation during rest in terms of decreased parasympathetic tone and increased sympathetic tone. Key words: Stress, Parasympathetic tone, Hyperandrogenism, Heart rate variability, Polycystic ovarian syndrome

The Fast Fourier Transform (FFT) method for solving the 1-D heat diffusion equation offers an efficient approach for resolving partial differential equations (PDEs) with various time steps . FFT is used to transform the 1-D heat diffusion equation into the frequency domain and back to the time domain through inverse FFT. Using mathematical modeling with initial and Dirichlet boundary conditions, the numerical solutions produced by FFT are compared with analytical solutions. The accuracy of the method is validated using MAE and MSE calculated in Matlab. At several time intervals , the obtained MAE and MSE values indicate a good agreement between the numerical and analytical solutions, with very small errors. Numerical stability analysis confirms the reliability of the FFT method across various The variation in time step has a significant impact on the accuracy and stability of the solution. Smaller time steps improve accuracy and stability but require longer computation times. The optimal time step selected in this study is Increasing the number of discretization points also enhances accuracy but implies an increase in computational load and memory usage. The FFT method demonstrates good numerical consistency with increasing

Central Java Province is a potential area that has an important role in national food production. El Nino and La Nina events have a very large impact if they occur in Indonesia, especially in Central Java Province. This study aims to analyze the impact of El Nino and La Nina events specifically in Central Java Province where the areas more dominantly affected by El Nino and La Nina. The research location uses 3 rainfall stations, namely the Tunggal Wulung Meteorological Station, Tegal Maritime Meteorological Station, and Tanjung Emas Maritime Meteorological Station. The method used is the Fast Fourier Transform (FFT) method and the long periodogram. The results showed that the periods of El Nino and La Nina phenomena recurring using the FFT method are forecasts for the periods 2.2428, 2.8036, and 3.7381 years. While using the lom periodogram method, namely in the periods of 2,480, 2,621, and 3:16 years. The results of the analysis of the FFT method obtained results that varied in the height of rainfall at the 3 stations, while the results of the analysis using the periodogram log showed that the Tunggal Wulung rain station had the highest peak rainfall. This study concludes that there are variations in the peak incidence using either the slow periodogram or the FFT method. However, both of these methods and based on the BMKG and TRMM, the Tunggal Wulung Meteorological Station has the highest peak between Tegal Station and Tanjung Emas Station.

To test the autonomic control of cardiovascular reflexes and heart rate variability (HRV) at rest and during orthostatic stress in narcolepsy with cataplexy (NC). Ten NC patients with a hypocretin deficit and 18 control subjects underwent head-up tilt test (HUTT), Valsalva manoeuvre, deep breathing and cold face under controlled laboratory conditions. Heart rate variability (HRV) was analysed during supine rest and HUTT considering the normalized unit of LF and HF power (LFnu; HFnu), using autoregressive (AR) and fast Fourier transform (FFT) algorithms. Cardiovascular changes during HUTT, Valsalva manoeuvre, deep breathing, isometric handgrip and cold face were normal and comparable in the two groups. AR and FFT analysis showed an increased LF/HF ratio in NC patients during supine rest. As expected, LFnu increased and HFnu decreased in the control group during HUTT, but did not change in narcoleptics being comparable to values in the supine condition. NC patients showed an increased sympathetic drive on heart rate (HR) in the supine condition that did not further increase during HUTT. These results suggest the proper functioning of cardiovascular reflexes in NC but support an impairment of HR modulation at rest in favour of an enhanced sympathetic activity.

Optical interferometry plays an important role in the topographical surface measurement and characterization in precision/ultra-precision manufacturing. An appropriate surface reconstruction algorithm is essential in obtaining accurate topography information from the digitized interferograms. However, the performance of a surface reconstruction algorithm in interferometric measurements is influenced by environmental disturbances and system noise. This paper presents a comparative analysis of three algorithms commonly used for coherence envelope detection in vertical scanning interferometry, including the centroid method, fast Fourier transform (FFT), and Hilbert transform (HT). Numerical analysis and experimental studies were carried out to evaluate the performance of different envelope detection algorithms in terms of measurement accuracy, speed, and noise resistance. Step height standards were measured using a developed interferometer and the step profiles were reconstructed by different algorithms. The results show that the centroid method has a higher measurement speed than the FFT and HT methods, but it can only provide acceptable measurement accuracy at a low noise level. The FFT and HT methods outperform the centroid method in terms of noise immunity and measurement accuracy. Even if the FFT and HT methods provide similar measurement accuracy, the HT method has a superior measurement speed compared to the FFT method.

Effect of aggregate shapes on local fields in 3D mesoscale simulations of the concrete creep behavior

Context Heart rate variability (HRV) can monitor cardiac autonomic control. Sympathovagal imbalance is expected after fentanyl/propofol induction. Aim The aim of the study was to investigate the effects of intravenous midazolam on HRV and whether it prevents the sympathovagal imbalance caused by fentanyl/propofol induction. Settings and design This is a controlled, randomized, double-blinded study. Patients and methods The study included 50 patients undergoing knee arthroscopies under general anesthesia. Powers of low-frequency (LF: 0.04-0.15 Hz) and high-frequency (HF: 0.15-0.4 Hz) components of HRV, total power (TP), and LF/HF ratio were recorded using MemCalc software. Patients received midazolam 0.05 mg/kg (midazolam group) or an equivalent volume of normal saline (control group), followed by fentanyl 1 mcg/kg and then propofol 2 mg/kg intravenously. Statistical analysis The Mann-Whitney U-test and two-way repeated analysis of variance, followed by Bonferroni correction as a post-hoc test, were used to analyze the data. Results Midazolam induced significant decrease in TP and HF powers, with unchanged LF power and LF/HF ratio. Fentanyl induced significant decrease in TP and LF powers with unchanged HF power and LF/HF ratio in both groups. Propofol induced a significant decrease in TP, HF, and LF powers in both groups. Propofol decreased the LF/HF ratio significantly in the control group but not in the midazolam group. Conclusion Midazolam premedication induced significant decrease in TP and HF powers without changes in LF power or LF/HF ratio. When fentanyl and propofol were given, midazolam was capable of modulating the net effects of both drugs on the HRV by minimizing the decrease in LF power to keep the LF/HF ratio unchanged. This modulatory effect of midazolam works in favor of maintaining the sympathovagal balance.