Time-variant power spectrum analysis for the detection of transientepisodes in HRV signal

A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the heart rate variability (HRV) signal. The power spectrum is calculated from the AR coefficients derived from each single RR interval considered. Time-variant AR coefficients are determined through adaptive parametric identification with a forgetting factor which obtains weighted values on a running temporal window of 50 preceding measurements. Power spectrum density (PSD) is hence obtained at each cardiac cycle, making it possible to follow the dynamics of the spectral parameters on a beat-by-beat basis. These parameters are mainly the LF (low-frequency) and the HF (high-frequency) powers, and their ratio, LF/HF. These together account for the balanced sympatho-vagal control mechanism affecting the heart rate. This method is applied to subjects suffering from transient ischemic attacks. The time variant spectral parameters suggest an early activation of LF component in the HRV power spectrum. It precedes by approximately 1.5-2 min the tachycardia and the ST displacement, generally indicative of the onset of an ischemic episode     

Comparison of detrended fluctuation analysis and spectral analysis for heart rate variability in sleep and sleep apnea

Sleep has been regarded as a testing situation for the autonomic nervous system, because its activity is modulated by sleep stages. Sleep-related breathing disorders also influence the autonomic nervous system and can cause heart rate changes known as cyclical variation. We investigated the effect of sleep stages and sleep apnea on autonomic activity by analyzing heart rate variability (HRV). Since spectral analysis is suited for the identification of cyclical variations and detrended fluctuation analysis can analyze the scaling behavior and detect long-range correlations, we compared the results of both complementary techniques in 14 healthy subjects, 33 patients with moderate, and 31 patients with severe sleep apnea. The spectral parameters VLF, LF, HF, and LF/HF confirmed increasing parasympathetic activity from wakefulness and REM over light sleep to deep sleep, which is reduced in patients with sleep apnea. Discriminance analysis was used on a person and sleep stage basis to determine the best method for the separation of sleep stages and sleep apnea severity. Using spectral parameters 69.7% of the apnea severity assignments and 54.6% of the sleep stage assignments were correct, while using scaling analysis these numbers increased to 74.4% and 85.0%, respectively. We conclude that changes in HRV are better quantified by scaling analysis than by spectral analysis.     

Reducing the effect of respiration in baroreflex sensitivity estimation with adaptive filtering

Cardiac baroreflex is described by baroreflex sensitivity (BRS) from blood pressure and heart rate interval (RRi) fluctuations. However, respiration affects both blood pressure and RRi via mechanisms that are not necessarily of baroreflex origin. To separate the effects of baroreflex and respiration, metronome-guided breathing in a high frequency band (HF, 0.25-0.4 Hz) and a low frequency spectral band (LF, 0.04-0.15 Hz) have therefore been commonly used for BRS estimation. The controlled breathing may, however, change the natural functioning of the autonomic system and interfere BRS estimates. To enable usage of spontaneous breathing, we propose an adaptive LMS-based filter for removing the respiration effect from the BRS estimates. ECG, continuous blood pressure and respiration were measured during 5 min spontaneous and 5 min controlled breathing at 0.25 Hz in healthy males (n = 24, 33+/-7 years). BRS was calculated with spectral methods from the LF band with and without filtering. In those subjects whose spontaneous breathing rate was <0.15 Hz, the BRS(LF) values were overestimated, whereas the adaptive filtering reduced the bias significantly. As a conclusion, the adaptive filter reduces the distorting effect of respiration on BRS values, which enables more accurate estimation of BRS and the usage of spontaneous breathing as a measurement protocol.     

基于受限玻尔兹曼机的语音带宽扩展

语音带宽扩展是为了提高语音质量,利用语音低频和高频之间的相关性重构语音高频的一种技术。高斯混合模型法是语音带宽技术中被广泛应用的一种方法,但是,由于该方法假设语音高频、低频服从高斯分布,且只表征了语音低频、高频之间的线性关系,从而导致合成的高频语音出现失真。因此,该文提出一种基于受限玻尔兹曼机的方法,该方法利用两个高斯伯努利受限玻尔兹曼机提取语音低频和高频中蕴含的高阶统计特性;并利用前馈神经网络将语音低频高阶统计特性参数映射为高频高阶统计特性参数。这样,通过提取语音低频和高频中蕴含的高阶统计特性,该方法可以深层挖掘语音高频和语音低频之间的实际关系,从而更加准确地模拟频谱包络分布,合成质量更高的语音。客观测试、主观测试结果表明,该方法性能优于传统的高斯混合模型方法。     

Pole-tracking algorithms for the extraction of time-variant heartrate variability spectral parameters

Various algorithms of autoregressive (AR) recursive identification make it possible to evaluate power spectral distribution in correspondence with each sample of a time series, and time-variant spectral parameters can be calculated through the evaluation of the pole positions in the complex z-plane. In traditional analysis, the poles are obtained by zeroing the denominator of the model transfer function, expressed as a function of the AR coefficients. Here, two algorithms for the direct updating and tracking of movements of poles of an AR time-variant model on the basis of the innovation given to the coefficients are presented and investigated. The introduced algorithms are based upon (1) the classical linearization method and (2) a recursive method to compute the roots of a polynomial, respectively. Here, applications in the field of heart rate variability (HRV) signal analysis are presented and efficient tools are proposed for quantitative extraction of spectral parameters (power and frequency of the low-frequency (LF) and high-frequency (HF) components) for the monitoring of the action of the autonomic nervous system in transient pathophysiological events. These computational methods seem to be very attractive for HRV applications, as they inherit the peculiarity of recursive time-variant identification, and provide a more immediate comprehension of the spectral process characteristics when expressed in terms of poles and AR spectral components     

Unique very low-frequency heart rate variability during deep sleep in humans

We investigate heart rate variability (HRV) in the very low-frequency (VLF) range (0.003-0.04 Hz) during deep sleep in good sleepers. Spectral analysis of HRV during deep sleep reveals consistent peaks at <0.04 Hz. By using wavelet analysis, we find both stationary and nonstationary periodic patterns in the VLF range, the presence of which has been discussed but has not been fully established to date. Although the mechanism(s) behind the unique VLF oscillations remain to be fully explored, we conjecture that there is an endogenous rhythmic component in human HRV in the VLF range. Further, our results also suggest a need for caution in the interpretation of the VLF spectral power in HRV during deep sleep.     

Dominant frequency analysis of EEG reveals brain's response duringinjury and recovery

A new method of monitoring and analyzing electroencephalogram (EEG) signals during brain injury is presented, EEG signals are modeled using the autoregressive (AR) technique to obtain the frequencies where there are peaks in the spectrum. The powers at these dominant frequencies are analyzed to reveal the state of brain injury during an experimental study involving progressive hypoxia, asphyxia, and recovery. Neonatal piglets (n=8) were exposed to a sequence of 30 min of hypoxia (10% oxygen), 5 min of room air, and 7 min of asphyxia. They then received cardiopulmonary resuscitation and were subsequently monitored for 4 h. An optimal AR model order of 6 was obtained for these data, resulting in 3 dominant frequencies. These dominant frequencies, referred to as the low, medium, and high frequency components, fell in the bands 1.0-5.5 Hz, 9.0-14.0 Hz, and 18.0-21.0 Hz, respectively. A remarkable feature of the authors' data is the spectral dispersion, or diverging trends in the 3 frequency bands. During hypoxia, the relative powers of the medium and high-frequency components of EEG increased up to 160% and 176%, from their respective baseline values. During the first minute of asphyxia the medium- and high-frequency powers (relative to baseline) increased by 280-400%. The power in all 3 frequency components went down to nearly zero within 40-80 s of asphyxia. During recovery, the phenomenon of burst-suppression was clearly exhibited in the low-frequency component. A new index, called mean normalized separation, representing the degree of disproportionality in the recovery of powers of the 3 dominant components relative to their mean recovered power, is presented as a possible single indicator of electrical function recovery. In conclusion, dominant frequency analysis helps reveal the brain's graded electrical response to injury and recovery     

Multivariate Decomposition of Arterial Blood Pressure Variability for the Assessment of Arterial Control of Circulation

In order to analyze the information carried by arterial blood pressure (ABP) variability, a multivariate parametric model of interactions involving systolic ABP (SAP), diastolic ABP (DAP), pulse pressure (PP), heart period (HP), and respiration is proposed. The model defines SAP as sum of the preceding DAP and PP values; DAP model accounts for arterial baroreflex, diastolic runoff; PP reflects changes in stroke volume related to respiration and HP, afterload; equation residuals reveal other vascular and cardiac output modulations. The model was applied to data from nine young volunteers (aged 29plusmn6 years) during supine cycling at 10%, 20%, and 30% of their maximum effort. Significant basal values and changes across the epochs of the experiment were found in all hemodynamic parameters describing fast, beat-by-beat responses; in SAP and PP total power, DAP low- and high-frequency power (LF, HF), PP very low frequency (VLF), and LF and HF power. A primary role of vascular control through DAP and PP was emphasized by the considered feedbacks and the model residuals. The model proved to be able to assess beat-by-beat cardiovascular interactions and offer a comprehensive view of arterial tree control.     

Broad-band analysis of VLF/LF aircraft wire antennas

The broad-band response of a VLF/LF dual-wire aircraft antenna is analyzed. The impedance properties and the induced currents on the two wires of different lengths are obtained via a superposition procedure in which the original problem is split into two transmission-line (differential-mode current) problems and two antenna (common-mode current) problems. Results for the input admittance and short-circuit current of a representative VLF/LF dual-wire antenna are presented.     

Stress control of silicon nitride films deposited by plasma enhanced chemical vapor deposition

Stress controllable silicon nitride(Si Nx) films deposited by plasma enhanced chemical vapor deposition(PECVD) are reported. Low stress Si Nx films were deposited in both high frequency(HF) mode and dual frequency(HF/LF) mode. By optimizing process parameters, stress free(-0.27 MPa) Si Nx films were obtained with the deposition rate of 45.5 nm/min and the refractive index of 2.06. Furthermore, at HF/LF mode, the stress is significantly influenced by LF ratio and LF power, and can be controlled to be 10 MPa with the LF ratio of 17% and LF power of 150 W. However, LF power has a little effect on the deposition rate due to the interaction between HF power and LF power. The deposited Si Nx films have good mechanical and optical properties, low deposition temperature and controllable stress, and can be widely used in integrated circuit(IC), micro-electro-mechanical systems(MEMS) and bio-MEMS.     

基于MATLAB的VLF/LF通信系统仿真

由于大气无线电噪声所涉及的现象非常复杂,观测结果又具有局限性,所以它对VLF／LF(甚低频／低频)通信系统性能影响的理论分析比较困难。本文运用MATLAB提供的Simulink动态仿真平台对大气噪声环境下的VLF／LF通信系统误码性能进行了仿真研究,并结合实例给出了系统的仿真结果,验证了该仿真系统的可行性。     

A wavelet-based heart rate variability analysis for the study of nonsustained ventricular tachycardia

It has been reported that the sympathovagal balance (SB) can be quantified by heart rate (HR) via the low-frequency (LF) to high-frequency (HF) spectral power ratio LF/HF. In this paper, an investigation of the relationship between the autonomic nervous system (ANS) and non-sustained ventricular tachycardia (NSVT) is presented. A wavelet transform (WT)-based approach for short-time heart rate variability (HRV) assessments is proposed for this aspect of analysis. The study was conducted on an RR-interval database consisting of 87 NSVT, 61 ischemic and five normal episodes. First, instantaneous SB estimates were generated by the proposed method. Then, waveforms of the WT-based SB evolutions were quantitatively examined. Numerical results showed that while a majority of SB waveforms (about 71%) derived from the non-NSVT population (i.e., ischemic and normal) appeared to come near oscillating with certain fixed levels, approximate 75% of SB evolutions underwent significantly rapid increases prior to the onset of NSVT, suggesting that an abrupt sympathovagal imbalance might partly account for the occurrence of NSVT.     

Wavelet decomposition of cardiovascular signals for baroreceptor function tests in pigs

In this paper, the discrete wavelet transform (DWT) was applied to analyze the fluctuations in RR interval and systolic arterial pressure (SAP) recorded from eight alpha-chloralose anesthetized pigs. Our aim was to characterize the autonomic modulation before and after cardiac autonomic blockade and during baroreflex function tests. The instantaneous power of decomposed low-frequency (LF) and high-frequency (HF) components was used for a time-variant spectral analysis. Our results suggested that transient events and changes in autonomic modulation were detected with high temporal resolution. A nonlinear relationship between RR interval and SAP during pharmacologically induced changes in blood pressure was found, when the superimposed effect of respiratory sinus arrhythmia was removed. In addition, the baroslopes were nearly linear when both the LF and HF components were removed using DWT decomposition.     

24 h sequential spectral analysis of arterial blood pressure andpulse interval in free-moving subjects

A procedure for the 24 h tracking of the 0.25, 0.1, and 0.05 Hz oscillations in blood pressure (BP) and pulse interval (PI) in ambulant subjects has been developed. It includes: 1) sampling of a 24 h intra-arterial BP recording, extraction of the systolic (S) and diastolic (D) BP and PI from each heart beat followed by storage into separate series; 2) high-pass filtering and a splitting of each series into consecutive records of 256 values; 3) estimation of power spectral density (PSD) via FFT in each stationary record, and finally, computation of the power of each target oscillation. Using this procedure we analyzed data from ten hospitalized free-moving subjects in whom BP was recorded by the Oxford technique. The results revealed different patterns of the 0.25, 0.1, and 0.05 oscillations over the day-night cycle, showing a differentiated involvement during the 24 h of the mechanisms responsible for such rhythmic phenomena. Moreover, in order to reinforce the meaning of the obtained results and to exclude the possible negative effects due to the drawbacks typical of the FFT algorithm, we also performed a second spectral estimate based on the AR modeling. The obtained results validates the FFT approach.     

Steerable ELF/VLF radiation produced by an array of ionospheric dipoles generated from HF heating

A very low frequency (VLF) or extremely low frequency (ELF) dipole source has been created within the lower ionosphere by modulating the atmospheric dynamo currents with a ground-based high power HF source from the Arecibo Observatory. The authors and their colleagues have demonstrated that ELF or VLF generated in this way and injected into the earth-ionosphere waveguide could be received a few thousand kilometers away. The injection properties due to an array of ionospheric dipoles as a function of array geometry and element currents that will allow steerable ELF/VLF radiation within the earth-ionosphere waveguide are investigated theoretically. The ionospheric array factors for a linear and a planar array of Hertzian dipole sources are developed and their properties examined. The principle of pattern multiplication is then applied to include the effect of the ionospheric array element. This provides a means for predicting the field strengths at a remote receiving site due to a steerable linear or planar array of ionospheric sources generated by high power HF periodic plasma heating.     

心肌缺血患者心率变异信号的现代谱分析法

采用自己研制的心电信号采集系统,将心电机的模拟信号放大滤波后,送入计算机中的采集卡中,采样频率设为1 kHz,连续采集5 min的心电信号并保存于硬盘中。利用C 编写了采集分析软件,用现代谱分析法和傅里叶(FFT)分析法,分析了19例正常人和7例心肌缺血患者心率变异信号的VLF/HF值。可以看出,心肌缺血患者和正常人的VLF/HF值有明显的差异。研究结果表明,谱分析法是分析心肌缺血患者自主神经异常的有效手段。     

On the tracking of rapid dynamic changes in seizure EEG

Estimation of autospectra and coherence and phase spectra of the seizure electroencephalograph (EEG), using the fast Fourier transform (FFT) technique, will cause smearing of the rapid dynamic changes which occur during the seizure. This is inherent to FFT spectral estimation, due to the averaging process which is necessary in order to get consistent spectral estimates. A different approach suggested in the present study is to carry out multivariate autoregressive modeling of the multichannel seizure EEG, combined with adaptive segmentation. In order to obtain good estimates in cases of short record length, the vectorial autoregressive (AR) modeling was based on residual energy ratios. The method has been tested on multichannel seizure EEG recordings from rats with focal epilepsy, caused by intracerebral administration of Kainic acid, and in-depth EEG recordings in patients with temporal lobe epilepsy     

基于频谱特征的脑皮层动静脉分离

光学功能成像是一种基于内源信号的功能映射方法,成像系统所采集到的脑皮层图像序列含有丰富的生理信号.本文利用心跳和呼吸引起的振荡信号的谱值特征实现了动静脉的分离.文中首先采用阈值分割和区域增长的方法对脑皮层的血管网络进行了提取,然后根据动脉波动信号频率分布在5~6 Hz之间而静脉波动信号频率分布在1~2 Hz之间的生理特征,分别计算其谱值,依据各信号谱值在特定频谱段内所占的功率谱百分比的不同实现了动脉和静脉的分离.最后,本文讨论了动、静脉中脉搏、呼吸以及0.1 Hz频谱分量的谱值和相位对动静脉分离的影响和潜在利用价值.     

低频/甚低频电磁脉冲测量系统研究

为了准确地测量电磁脉冲（electromagnetic pulse,EMP）的波形,开展低频/甚低频（low-frequency/very low-frequency,LF/VLF）EMP的形成和传播机理研究,识别不同EMP的特征,并以此为依据来识别、确认雷电及核爆炸等现象,提出了一种高分辨率的EMP原始波形测量系统方案,同时针对LF/VLF这一较低的频段提出了一套有效的系统标校方法,实现了对EMP的连续、准确测量和快速有效判别,并能通过网络实时上传数据.系统采用正交环磁场天线和平板电容电场天线实现信号的接收,设计了低噪声高保真的信道调理电路和高速数据采集电路来实现信号的采集,利用高精度的授时模块为EMP信号标记时间戳,最后结合多点监测波形实现EMP定位估计.实测结果表明:该系统能够给出高分辨率、高精度的LF/VLF EMP波形;利用该系统组网可以实现远距离EMP源的定位,定位精度与目前近距离的定位手段相当.通过长期的运行,验证了该系统具有高可靠、低失真、判别准确、实时性强等特点.