Analysis of beat-to-beat variability of frequency contents in theelectrocardiogram using two-dimensional Fourier transforms

Late potentials are very small signals (1-20 μV) in the surface ECG with high-frequency components, which are found in patients prone to sustained ventricular tachycardia. Evaluation of these signals requires either very sophisticated recording techniques for single-beat analysis or signal averaging. Signal averaging, however, might disregard information about risk stratification. Therefore, the authors developed the Single-Beat Spectral Variance (SBSV) based on two-dimensional (2-D) Fourier transform of 80 ms segments of 128 consecutive beats. This approach depicts the beat-to-beat variability of the frequency contents of these ECG segments. An index function enables an objective detection of late potentials. The authors investigated 35 patients after myocardial infarction and sustained ventricular tachycardia (Group 1), 50 patients after myocardial infarction without ventricular arrhythmias (Group 2) and ten healthy volunteers, SBSV classified 29 of 35 patients (83%) of Group 1 as pathologic, 14 of these 29 patients (48%) exclusively on the basis of marked Wenckebach-like conduction pattern. In Group 2, only five of 50 patients showed abnormal SBSV. In Group 3, the authors found no pathologic result. Thus, SBSV is a promising new method to investigate late potentials inpatients after myocardial infarction, SBSV-contains not only the results of frequency analysis after signal averaging, but also evaluates variable ECG components     

Variability of the QRS signal in high-resolution electrocardiograms and magnetocardiograms

The variability of electric and magnetic signals from the heart during the depolarization phase is investigated. A signal processing method is developed, which provides estimates for the beat-to-beat variability of the QRS-complex. The method is based on the decomposition of the depolarization signal into bandpass signals by means of the Morlet wavelet transform. The beat variability of the depolarization signal is estimated by normalized variances of the envelope and instantaneous frequency of bandpass signals. Time intervals of the bandpass filtered depolarization signals having a high signal-to-noise ratio are selected applying an analysis based on phase statistics. The method was tested by computer simulation and experimental data taken from electrocardiographic and magnetocardiographic measurements of healthy persons and patients prone to malignant ventricular tachycardia (VT) or ventricular fibrillation (VF). Results suggest that the calculated variance parameters permit the characterization of beat variable depolarization signals and distinguish VT/VF patients from healthy persons.     

Analysis of abnormal signals within the QRS complex of thehigh-resolution electrocardiogram

Presents a new, quantitative approach to measuring abnormal intra-QRS signals, using the high-resolution electrocardiogram (HRECG). These signals are conventionally known as QRS “notches and slurs.” They are measured qualitatively and form the basis for the ECG identification of myocardial infarction. The HRECG is used for detection of ventricular late potentials (LP), which are linked with the presence of a reentry substrate for ventricular tachycardia (VT) after a myocardial infarction. LP's are defined as signals from areas of delayed conduction which outlast the normal QRS period. The authors' objective is to quantify very low-level abnormal signals that may not outlast the normal QRS period. In this work, abnormal intra-QRS potentials (AIQP) were characterized by removing the predictable, smooth part of the QRS from the original waveform. This was represented as the impulse response of an ARX parametric model, with model order selected empirically from a training data set. AIQP were estimated using the residual of the modeling procedure. Critical AIQP parameters to separate VT and non-VT subjects were obtained using discriminant functions. Results suggest that AIQP indexes are a new predictive index of the HRECG for VT. The concept of abnormal intra-QRS potentials permits the characterization of pathophysiological signals contained wholly within the normal QRS period, but related to arrhythmogenesis. The new method may have other applications, such as detection of myocardial ischemia and improved ECG identification of the site of myocardial infarction, particularly in the absence of Q waves     

Phase and group-delay characteristics of signal-averagedelectrocardiograms from patients with ventricular tachycardia

Fourier analysis of the signal-averaged ECG (SAECG) has previously revealed significant differences in magnitude spectra that differentiate patients with ventricular tachycardia (VT) from those without VT. To determine additional distinguishing features in the frequency domain, the authors analyzed phase spectra of SAECG's of sinus beats from 57 patients with VT, 65 without VT, and 20 normal controls. Unwrapped phase spectra from SAECG's of the entire cardiac cycle were calculated with respect to three fiducial points: onset of the P and Q waves, and the negative of the slope of the phase (group delay for frequencies in the band, which accounted for 97.5% of the energy in the vector magnitude of the Frank SAECG leads. Phase spectra of SAECG's from patients with VT differed from the non-VT patients at frequencies ⩾21 Hz (p=0.000039) for the P-wave fiducial, at frequencies ⩾60 Hz (p=0.00085) for the Q-wave fiducial, and at frequencies ⩾62 Hz (p=0.0035) for the 97.5% energy fiducial. Group delays in SAECG's from patients with and without VT differed from 10 to 26 Hz (p=0.000016) for the P-wave fiducial, and from 14 to 24 Hz (p=0.00000070) for the Q-wave fiducial. Group delays with respect to the Q-wave fiducial in the VT patients in the 14-24 Hz band were, on average, 9 ms and 5 ms longer than those of the non-VT's and normals, respectively. Thus, phase spectra of SAECG's contain previously undetected features that together with magnitude may be helpful in improving methods for stratifying the risk of VT     

A theoretical model of the high-frequency arrhythmogenic depolarization signal following myocardial infarction

Theoretical body-surface potentials were computed from single, branching and tortuous strands of Luo-Rudy dynamic model cells, representing different areas of an infarct scar. When action potential (AP) propagation either in longitudinal or transverse direction was slow (3-12 cm/s), the depolarization signals contained high-frequency (100-300 Hz) oscillations. The frequencies were related to macroscopic propagation velocity and strand architecture by simple formulas. Next, we extended a mathematical model of the QRS-complex presented in our earlier work to simulate unstable activation wavefront. It combines signals from different strands with small timing fluctuations relative to a large repetitive QRS-like waveform and can account for dynamic changes of real arrhythmogenic micropotentials. Variance spectrum of wavelet coefficients calculated from the composite QRS-complex contained the high frequencies of the individual abnormal signals. We conclude that slow AP propagation through fibrotic regions after myocardial infarction is a source of high-frequency arrhythmogenic components that increase beat-to-beat variability of the QRS, and wavelet variance parameters can be used for ventricular tachycardia risk assessment.     

基于FPGA和DSP的遥测数据实时谱分析卡设计

为了实时分析遥测数据单位频带内信号谱信息随频率的变化情况,设计了一种遥测数据实时谱分析卡。设计采用FPGA+DSP系统架构,配合流水线作业的设计理念。振动信号功率谱密度（PSD）计算采用快速傅里叶变换法（FFT）,冲击信号冲击响应谱(SRS)采用递归数字滤波法,极大降低运算量,缩短谱分析的时间,从而实现对谱信息的实时性分析。测试结果表明,该谱分析卡可以在9ms内完成对一路高频振动数据的处理,在67ms内完成对一路冲击数据的处理,设计具有良好的实时性、稳定性和扩展性,在实际应用中得到较好的效果。     

Frequency spectra of ventricular tachycardia and sinus rhythm inhuman intracardiac electrograms-application to tachycardia detection forcardiac pacemakers

Presently available antitachycardia pacemakers detect ventricular tachycardia (VT) by measurement of the period of the intracardiac electrogram (EGM). The resulting inability to differentiate between VT and rapid normal sinus rhythm (NSR) can cause inappropriate pacemaker output, possibly initiating an arrhythmia where none existed previously. It is reported that FFT analysis of matched-pair NSR-VT EGM recordings from 33 patients revealed a mean (±SD) NSR-VT difference in the peak amplitude point of 8 (±7) Hz and a difference of 18 (±18) Hz in the -3 dB point. NSR-VT amplitude differences could be significantly increased by filtering over the range of greatest spectral differences. Variable-passband programmable filters could enhance VT detection in antitachycardia pacemakers     

Mirror electron microscope for inspecting nanometer-sized defects in magnetic media

We developed a mirror electron microscope (MEM) for the highly sensitive inspection of defects on the magnetic storage disks of commercial hard disk drives (HDDs). Magnetic fields recorded on a magnetic disk do not affect the MEM images for inspection. We used artificial defects in a detection sensitivity evaluation to test the effectiveness of our MEM inspection tool and found that it was sensitive enough to detect defects that were 67 nm in diameter and 7 nm in height. The size of a MEM image for a defect was eight times larger than the physical size measured by an atomic force microscope. The obtained sensitivity is beyond the resolution power of the objective lens of the MEM itself. This is because MEM images the distortion of static electrical potentials spread over a larger area than the physical size of a defect itself and the image is obtained in out-of-focus condition of an objective lens. The image acquisition time was 50 ms, which corresponded to the inspection time of 4 h for the full surface inspection of a 2.5 in. magnetic disk. MEM is a promising technique for conducting a highly sensitive defect inspection and a high throughput inspection simultaneously as compared with an SEM-based inspection.     

Late potential recognition by artificial neural networks

Ventricular late potentials (LPs) are high-frequency low-amplitude signals obtained from signal-averaged electrocardiograms (ECGs) [SAECGs]. LPs are useful in identifying patients prone to ventricular tachycardia (VT), spontaneous or inducible during electrophysiology testing. A combination of self-organizing and supervised artificial neural network (ANN) models was developed to identify patients with a positive electrophysiology (PEP) test for inducible ventricular tachycardia from patients with a negative electrophysiology (NEP) test using LPs. We have added morphology information of vector magnitude waveform to an original set of three time-domain features of LPs, which are total QRS duration (TQRSD), high-frequency low-amplitude signal duration (HFLAD), and root-mean-square voltage (RMSV). Pattern recognition results from an ANN model with this combination feature set are superior to the results from Bayesian classification model based on conventional three time-domain features of SAECG. In order to increase the robustness of the recognition, a filtered QRS offset point is randomly shifted ±8 ms to form a fuzzy training set, which was to simulate the possible error in detecting QRS offset point of filtered SAECG. We also found that nonlinear transformation through the hidden layer of developed ANN model could increase Euclidean distance between PEP and NEP patterns     

基于FPGA实现PN码快速捕获方案的设计

文章基于离散时间信号处理的分析方法,对多普勒频移影响PN码的性能进行了讨论。详细分析了部分数字相关器与FFT结合的频响特性并进行了系统仿真。在此基础上,提出了对存在较大多普勒频移的长伪随机码系统,采用FPGA实现部分数字相关器与FFT频率校正技术相结合的伪码捕获算法,实现较短时间捕获PN码的方案。     

基于FFT校频的分段匹配滤波器性能分析

为了对动态PN码捕获中使用的分段匹配滤波器的设计进行指导,在建立其数学模型的基础上,分析了分段数、FFT点数与载波频偏对滤波器性能的影响。结果表明,增加分段数可以减小载波频偏对相关峰的影响;增加FFT点数可以提高频偏校正的精度;在环境噪声为高斯白噪声情况下,存在最佳的分段数和FFT点数组合,可以用最小运算量达到最佳捕获效果。     

少模光纤通信频域均衡中的大点数FFT设计

为了减小频域均衡系统电路实现的功耗和面积,满足长距离少模光纤通信对均衡器的要求,对关键环节快速傅里叶变换(FFT)电路的实现进行了研究,采用2维分解算法将大点数的FFT运算转换为小点数FFT处理器的设计,降低了硬件复杂度。设计了基于现场可编程门阵列的高速蝶形运算核,实现了16384点FFT的2维R22SDF结构,提高存储器的资源利用率,减少了复数乘法器的使用;进行了理论分析和实验验证,取得了不同时钟频率下的电路结构占用资源的数据。结果表明,FFT运算器的正确性得到验证,该FFT运算器能够适应少模光纤通信系统中优化频域均衡电路结构的要求,能够实现200MHz数据传输速度的频域均衡实时处理。     

Processing of pulse oximeter data using discrete wavelet analysis

A wavelet-based signal processing technique was employed to improve an implantable blood perfusion monitoring system. Data was acquired from both in vitro and in vivo sources: a perfusion model and the proximal jejunum of an adult pig. Results showed that wavelet analysis could isolate perfusion signals from raw, periodic, in vitro data as well as fast Fourier transform (FFT) methods. However, for the quasi-periodic in vivo data segments, wavelet analysis provided more consistent results than the FFT analysis for data segments of 50, 10, and 5 s in length. Wavelet analysis has thus been shown to require less data points for quasi-periodic data than FFT analysis making it a good choice for an indwelling perfusion monitor where power consumption and reaction time are paramount.     

Correspondence between simple 3-D MRI-based computer models and in-vivo EP measurements in swine with chronic infarctions

The aim of this paper was to compare several in-vivo electrophysiological (EP) characteristics measured in a swine model of chronic infarct, with those predicted by simple 3-D MRI-based computer models built from ex-vivo scans (voxel size <1 mm(3)). Specifically, we recorded electroanatomical voltage maps (EAVM) in six animals, and ECG waves during induction of arrhythmia in two of these cases. The infarct heterogeneities (dense scar and border zone) as well as fiber directions were estimated using diffusion weighted DW-MRI. We found a good correspondence (r = 0.9) between scar areas delineated on the EAVM and MRI maps. For theoretical predictions, we used a simple two-variable macroscopic model and computed the propagation of action potential after application of a train of stimuli, with location and timing replicating the stimulation protocol used in the in-vivo EP study. Simulation results are exemplified for two hearts: one with noninducible ventricular tachycardia (VT), and another with a macroreentrant VT (for the latter, the average predicted VT cycle length was 273 ms, compared to a recorded VT of 250 ms).     

A comparison between Walsh and Fourier analysis of the electroencephalogram for tracking the effects of anesthesia

The effects that anesthesia has on the surgical patient can be characterized with the electroencephalogram (EEG). These effects are typically quantified through frequency analysis of the EEG signal. The fast Fourier transform (FFT) is usually employed for this purpose. In recent years, the fast Walsh transform (FWT) has been proposed as an alternative to the FFT for signal analysis because it is computationally more efficient, requiring less time to complete on a digital computer. This paper statistically evaluates the quantitative and dynamic differences between the results of Walsh and Fourier analysis of the EEG done for the purpose of characterizing the effects of anesthesia. This paper shows that there are quantitative differences between the results of the two frequency analysis techniques but they are dynamically equivalent, both showing essentially the same changes due to the effects of anesthesia. The efficiency of the FWT has been reconfirmed. These results support the use of the FWT in place of the FFT for tracking the effects of anesthesia on surgical patients with the EEG.     

基于全相位FFT的稳健型时间调制阵列测向

基于谐波特征分析的时间调制阵列测向方法的正确性与精度严重依赖接收谐波的估计精度. 传统的离散傅里叶变换(discrete Fourier transform, DFT)或快速傅里叶变换(fast Fourier transform, FFT)在估计谐波的幅相时,由于信号频率通常偏离采样频率的整数倍,会形成栅栏效应,从而引起基于谐波特征分析的时间调制阵列测向的精度降低甚至失效. 针对该问题,本文将全相位FFT引入二单元时间调制阵列接收谐波的分析中,通过提升谐波幅相估计的鲁棒性来提升时间调制阵列测向方法的稳健性. 仿真结果表明,当信号的载频为频谱分辨率的任意小数倍时,提出的全相位FFT时间调制阵列测向方法均能正确测向,且随着信噪比的增加,测向均方根误差收敛至0. 本文工作提升了基于谐波特征分析的单通道时间调制阵列测向方法的稳定性。     

全新卫星双向时间比对调制解调器设计

卫星双向时间频率传递是目前被广泛应用的远距离高精度时间频率量值传递方法,其核心组成设备是双向时间比对调制解调器.文章介绍了由北京无线电计量测试研究所研制的卫星双向时间比对调制解调器,该设备采用直接序列扩频(DSSS)和二进制相移键控(BPSK)方式完成时间信号的调制,采用快速傅里叶变换(FFT)算法实现对信号的快速搜索和捕获;利用二阶锁频辅助三阶锁相环路达到动态性能和跟踪精度的平衡;采用二阶延迟锁定环(DLL)来实现对码相位的精密跟踪和测量.采用两个1.2m口径天线的双向比对地球站进行短基线卫星双向时间比对试验,试验结果表明当系统工作在2.5MChip/s码速率时,该调制解调器的时间比对精度(标准偏差(1σ))能够达到0.13ns.     

高动态短时突发通信系统的载波同步技术

载波同步是数据解调中的重要环节之一。由于高动态短时突发通信系统的通信时间极短,在算法观测时间内可认为频率无变化,因此可对载波频偏进行一次校频,使之快速落入锁相环快捕带内,然后利用锁相环进行跟踪以完成载波同步。实践表明:利用一种改进的FFT校频技术对载波频偏进行一次校频,能使载波频偏快速落入锁相环快捕带内。最后分别对改进的FFT校频技术及锁相环进行了仿真分析,结果表明该方法在低信噪比下仍具有良好的性能。     

Empirical rules for the selection of parameters for auto-regressive spectral analysis of biomedical rhythms

Auto-regressive modelling provides an attractive method for the accurate estimation of multiple frequency components in short biological time-series comprising only a few cycles of data. The effects of increasing noise content, decreasing number of data points and different relative amplitudes of spectral components on the accuracy of frequency estimation are considered. The relationship between model order, sampling frequency and frequency discrimination between nearly equal components is demonstrated using digit blood-flow data, circadian rhythms and intestinal myoelectrical slow-waves. From these biomedical examples it is concluded that, by choosing parameters carefully, auto-regressive spectral analysis can be considerably superior to standard FFT methods for short time-series analysis.     

A Digital QRS Detector Based on the Principle of Contour Limiting

The article describes a detector for physiological phenomena, e.g., the QRS-complex, having a trigger accuracy of 0.5 ms. The configuration to be recognized first is preprocessed then fed into a pair of amplifiers with adjustable gain and offset, representing the upper and lower contour-limit derived from the actual signal. These signals are sampled and A/D converted, then stored in two memories during the ``read'-operation.