一种心电监测和房颤预警系统的研究

随着社会进步和经济的发展,在人们生活水平提高的同时,各种心血管疾病成为人类健康的隐形杀手。本文提出了一种基于嵌入式架构的便携式心电监测和房颤预警系统,实现了受试者心电信号实时采集监测的功能,采集数据通过无线网络传输至云端进行存储,监测者可以远程获取云上存储的心电监测数据,下载并采用基于主分量解析分析去获取受试者心电房颤的特征信息,准确判断受试者是否出现房颤的情况,从而实现受试者的心脏健康状况,监测结果可以在监测设备显示屏以及远程安卓手机的APP程序中进行显示。本研究所开发的系统具有成本低廉、操作简便、运行可靠等优势。     

Classification of paroxysmal and persistent atrial fibrillation in ambulatory ECG recordings

The problem of classifying short atrial fibrillatory segments in ambulatory ECG recordings as being either paroxysmal or persistent is addressed by investigating a robust approach to signal characterization. The method comprises preprocessing estimation of the dominant atrial frequency for the purpose of controlling the subbands of a filter bank, computation of the relative subband (harmonics) energy, and the subband sample entropy. Using minimum-error-rate classification of different feature vectors, a data set consisting of 24-h ambulatory recordings from 50 subjects with either paroxysmal (26) or persistent (24) atrial fibrillation (AF) was analyzed on a 10-s segment basis; a total of 212,196 segments were classified. The best performance in terms of area under the receiver operating characteristic curve was obtained for a feature vector defined by the subband sample entropy of the dominant atrial frequency and the relative harmonics energy, resulting in a value of 0.923, whereas that of the dominant atrial frequency was equal to 0.826. It is concluded that paroxysmal and persistent AFs can be discriminated from short segments with good accuracy at any time of an ambulatory recording.     

Noninvasive ECG as a tool for predicting termination of paroxysmal atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia and entails an increased risk of thromboembolic events. Prediction of the termination of an AF episode, based on noninvasive techniques, can benefit patients, doctors and health systems. The method described in this paper is based on two-lead surface electrocardiograms (ECGs): 1-min ECG recordings of AF episodes including N-type (not terminating within an hour after the end of the record), S-type (terminating 1 min after the end of the record) and T-type (terminating immediately after the end of the record). These records are organised into three learning sets (N, S and T) and two test sets (A and B). Starting from these ECGs, the atrial and ventricular activities were separated using beat classification and class averaged beat subtraction, followed by the evaluation of seven parameters representing atrial or ventricular activity. Stepwise discriminant analysis selected the set including dominant atrial frequency (DAF, index of atrial activity) and average HR (HRmean, index of ventricular activity) as optimal for discrimination between N/T-type episodes. The linear classifier, estimated on the 20 cases of the N and T learning sets, provided a performance of 90% on the 30 cases of a test set for the N/T-type discrimination. The same classifier led to correct classification in 89% of the 46 cases for N/S-type discrimination. The method has shown good results and seems to be suitable for clinical application, although a larger dataset would be very useful for improvement and validation of the algorithms and the development of an earlier predictor of paroxysmal AF spontaneous termination time.     

光学表面功率谱密度的表征

以硅基板镀制单层HfO2薄膜前后的表面微观形貌的变化为例,开展了光学表面功率谱密度的计算及表征研究。首先给出了一维功率谱密度(PSD1D)、二维功率谱密度(PSD2D)以及各向同性功率谱密度(PSDISO)的计算方法和具体步骤。然后使用原子力显微镜测量了硅基板镀膜前后在1 m1 m、5 m5 m、10 m10 m、20 m20 m四种扫描尺寸下的表面轮廓。在此基础上使用MATLAB编程计算得到这四种扫描尺寸下的PSDISO,对这些PSDISO使用几何平均算法拼接得到具有足够大频率范围的PSDISO-Combined。结果显示,硅基板镀膜前后的PSDISO-Combined在低频段基本相同,中高频段出现了明显差异。分析指出这是由镀膜后表面柱状晶体结构引起的。提出了对PSDISO在频域上积分得到表面均方根粗糙度ISO,再同由定义式计算得到的STD作对比的方法。计算得到的ISO与STD基本相同,验证了PSDISO计算方法的准确性。     

Phase-rectified signal averaging used to estimate the dominant frequencies in ECG signals during atrial fibrillation

Phase-rectified signal averaging (PRSA) is a technique recently introduced to enhance quasi-periodic signal components. An important parameter that can be extracted from surface ECG is the dominant frequency (DF) of atrial fibrillation (AF). AF signal components are always highly contaminated by the ventricular complexes, and the cancellation of these components is never perfect. The remaining artifacts tend to induce erroneous DF estimates. In this paper, we report on the use of PRSA in the context of noninvasive AF classification procedures for improving DF estimation. The potential of PRSA is demonstrated by experiments both on synthetic and clinical ECG signals.     

Frequency tracking of atrial fibrillation using hidden Markov models.

A hidden Markov model (HMM) is employed to improve noise robustness when tracking the dominant frequency of atrial fibrillation (AF) in the electrocardiogram (ECG). Following QRST cancellation, a sequence of observed frequency states is obtained from the residual ECG, using the short-time Fourier transform. Based on the observed state sequence, the Viterbi algorithm retrieves the optimal state sequence by exploiting the state transition matrix, incorporating knowledge on AF characteristics, and the observation matrix, incorporating knowledge of the frequency estimation method and signal-to-noise ratio (SNR). The tracking method is evaluated with simulated AF signals to which noise, obtained from ECG recordings, has been added at different SNRs. The results show that the use of HMM improves performance considerably by reducing the rms error associated with frequency tracking: at 4-dB SNR, the rms error drops from 0.2 to 0.04 Hz.     

Atrial activity extraction for atrial fibrillation analysis using blind source separation

This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA and VA present non-Gaussian distributions; and 3) the generation of the surface ECG potentials from the cardioelectric sources can be regarded as a narrow-band linear propagation process. To empirically endorse these claims, an ICA algorithm is applied to recordings from seven patients with persistent AF. We demonstrate that the AA source can be identified using a kurtosis-based reordering of the separated signals followed by spectral analysis of the sub-Gaussian sources. In contrast to traditional methods, the proposed BSS-based approach is able to obtain a unified AA signal by exploiting the atrial information present in every ECG lead, which results in an increased robustness with respect to electrode selection and placement.     

Characterization and optimization of optical pulse differentiation using spectral interferometry

A simple fiber-based spectral interferometry setup is implemented for characterizing and monitoring the amplitude and phase of ultrafast temporal waveforms generated by optical differentiation with a long-period fiber grating (LPFG). In particular, the system is applied to characterize subpicosecond odd-symmetry Hermite-Gaussian (HG) pulses, consisting of two /spl pi/ phase-shifted temporal lobes, obtained by temporal differentiation of Gaussian-like pulses. This technique is ideally suited for optimizing the experiment conditions (e.g., wavelength shifting between the input pulse and LPFG transmission characteristic) so as to achieve a nearly ideal odd-symmetry HG temporal waveform (with a sharp discrete /spl pi/ phase shift at its center), of potential interest as a higher order soliton in dispersion-managed optical communication systems.     

Interference rejection using the time-dependent constant modulusalgorithm (CMA) and the hybrid CMA/spectral correlation discriminator

Two new blind adaptive filtering algorithms for interference rejection using time-dependent filtering structures are presented. The time-dependent structure allows the adaptive filter to outperform the conventional adaptive filter implemented with a time-independent structure for filtering of cyclostationary communication signals. At the same time, the blind adaption algorithms allow the filters to operate without the use of an external training signal. The first algorithm applies the CMA to an unconstrained time-dependent filtering structure. The second algorithm applies the CMA to a spectral correlation discriminator, which is constrained to select signals with unique spectral correlation characteristics. Using computer simulations, it is shown that the blind time-dependent filtering algorithms can provide mean-square errors (MSEs) and bit error rates (BERs) that are significantly lower than the MSEs and BERs provided using conventional time-independent adaptive filters. It is also shown that these processors can outperform the nonblind training-sequence directed time-independent adaptive filter     

Characterization of in-building UHF wireless radio communicationchannels using spectral energy measurements

A simple, cost-effective means is developed to estimate the time-invariant wireless radio channel impulse response h(t) using only the magnitude of the channel transfer function, H(jw). The Hilbert transform is used to calculate the phase of H(jw) from its magnitude. Inverse discrete Fourier transformation (IDFT) of H(jw) yields h(t). The Hilbert transform relation is applicable provided H(jw) is a minimum phase transfer function. An experimental in-building wireless channel testbed was established, for which h(t) was determined over the 1000-2500 MHz range. Both line of sight (LOS) and non-LOS transmission was investigated. Good agreement was observed between values of h(t) calculated from measured values of H(jw) and from those based only on [H(jw)] and its Hilbert transform. Even when the minimum phase condition is violated, h(t) as calculated from [H(jw)] and its Hilbert transform provides a useful lower bound on the time-spread of h(t). The measurement of [H(jw)] is easily implemented using a signal source, receiving antenna, and spectrum analyzer. A personal computer and software are required to calculate the phase of H(jw) and its IDTF. Existing frequency-domain measurement schemes utilize a vector network analyzer to measure H(jw) (magnitude and phase angle). Such equipment is expensive, subject to transmitter-receiver crosstalk, and restrictive as to the relative locations of the transmitting and receiving antenna     

Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes

Currently, no reliable method exists to predict the onset of paroxysmal atrial fibrillation (PAF). We propose a predictor that includes an analysis of the R-R time series. The predictor uses three criteria: the number of premature atrial complexes (PAC) not followed by a regular R-R interval, runs of atrial bigeminy and trigeminy, and the length of any short run of paroxysmal atrial tachycardia. An increase in activity detected by any of these three criteria is an indication of an imminent episode of PAF. Using the Physionet database of the Computers in Cardiology 2001 Challenge, the predictor achieved a sensitivity of 89% and a specificity of 91%.     

Characterization of fiber Bragg gratings using spectral interferometry based on minimum-phase functions

The focus of this paper is on interferometric systems that utilize spectral interferometry based on minimum-phase functions (MPFs) to fully characterize any fiber-Bragg-grating (FBG) spectra without exceptions. The approach presented involves sending a broadband light source (e.g., a short laser pulse) into the FBG of interest and using an optical spectrum analyzer (OSA) to record the spectrum of the interference between the reflected pulse from the grating and the time-delayed version(s) of the original short pulse. The square root of this measured spectrum, which yields the Fourier-transform (FT) magnitude of the input-pulse-sequence electric-field envelope, is then processed to uniquely recover both the phase and the amplitude of the FBG spectrum. The underlying principle for this unique recovery is that by construction, the input pulse sequence sent to the OSA is close to an MPF; thus, it is possible to recover its FT phase spectrum using only the measurement of its FT magnitude spectrum. This is an important result since, by merely measuring the FT magnitude, the entire complex spectrum of the grating can be recovered. Furthermore, this technique can conveniently be used to simultaneously characterize more than one FBG, using a single FT magnitude measurement. This technique has important advantages over existing techniques: a higher resolution and the ability to use longer duration laser pulses.     

Study of the surface properties of thermally oxidized silicon using surface acoustic wave attenuation

In the separate media space charged coupled convolver, the interaction of a surface acoustic wave (SAW) with the free carriers in an adjacent semiconductor results in attenuation of the acoustic wave. The magnitude of the attenuation is dependent on the concentration of the free carriers near the surface. An externally applied d.c. voltage changes the surface carrier concentration and this change is reflected in SAW attenuation. Analysis of the SAW attenuation caused by a continuous d.c. field gives an estimate of the surface state density. The time required for the SAW attenuation to reach steady state after the semiconductor is driven into deep depletion is an indication of the rate of carrier generation in the depletion region. Transient effects have also been observed using a synchronously applied d.c. pulse.     

Characterization of HTRB stress effects on SiC MOSFETs using photon emission spectral signatures

This paper presents a reliability study of a 1.2 kV SiC MOSFET under HTRB (High Temperature Reverse Bias stress by the photon emission (PE) and the spectral photon emission (SPE) techniques. The electrical characteristics analysis suggests failures related to the PN junction degradation. This hypothesis is confirmed by the PE and SPE techniques.     

Sequential characterization of atrial tachyarrhythmias based on ECG time-frequency analysis

A new method for characterization of atrial arrhythmias is presented which is based on the time-frequency distribution of an atrial electrocardiographic signal. A set of parameters are derived which describe fundamental frequency, amplitude, shape, and signal-to-noise ratio. The method uses frequency-shifting of an adaptively updated spectral profile, representing the shape of the atrial waveforms, in order to match each new spectrum of the distribution. The method tracks how well the spectral profile fits each spectrum as well as if a valid atrial signal is present. The results are based on the analysis of a learning database with signals from 40 subjects, of which 24 have atrial arrhythmias, and an evaluation database with 211 patients diagnosed with atrial fibrillation. It is shown that the method robustly estimates fibrillation frequency and amplitude and produces spectral profiles with narrower peaks and more discernible harmonics when compared to the conventional power spectrum. The results suggest that a rather strong correlation exist between atrial fibrillation frequency and f wave shape. The developed set of parameters may be used as a basis for automated classification of different atrial rhythms.     

Comparison of atrial signal extraction algorithms in 12-lead ECGs with atrial fibrillation

Analysis of atrial rhythm is important in the treatment and management of patients with atrial fibrillation. Several algorithms exist for extracting the atrial signal from the electrocardiogram (ECG) in atrial fibrillation, but there are few reports on how well these techniques are able to recover the atrial signal. We assessed and compared three algorithms for extracting the atrial signal from the 12-lead ECG. The 12-lead ECGs of 30 patients in atrial fibrillation were analyzed. Atrial activity was extracted by three algorithms, Spatiotemporal QRST cancellation (STC), principal component analysis (PCA), and independent component analysis (ICA). The amplitude and frequency characteristics of the extracted atrial signals were compared between algorithms and against reference data. Mean (standard deviation) amplitude of QRST segments of V1 was 0.99 (0.54) mV, compared to 0.18 (0.11) mV (STC), 0.19 (0.13) mV (PCA), and 0.29 (0.22) mV (ICA). Hence, for all algorithms there were significant reductions in the amplitude of the ventricular activity compared with that in V1. Reference atrial signal amplitude in V1 was 0.18 (0.11) mV, compared to 0.17 (0.10) mV (STC), 0.12 (0.09) mV (PCA), and 0.18 (0.13) mV (ICA) in the extracted atrial signals. PCA tended to attenuate the atrial signal in these segments. There were no significant differences for any of the algorithms when comparing the amplitude of the reference atrial signal with that of the extracted atrial signals in segments in which ventricular activity had been removed. There were no significant differences between algorithms in the frequency characteristics of the extracted atrial signals. There were discrepancies in amplitude and frequency characteristics of the atrial signal in only a few cases resulting from notable residual ventricular activity for PCA and ICA algorithms. In conclusion, the extracted atrial signals from these algorithms exhibit very similar amplitude and frequency characteristics. Users of these algorithms should be observant of residual ventricular activities which can affect the analysis of the fibrillatory waveform in clinical practice.     

Discrimination of atrial fibrillation from regular atrial rhythmsby spatial precision of local activation direction

This study tests the hypothesis that atrial fibrillation (AFib) can be discriminated from regular atrial rhythms by a measure of the variation in local activation direction. Human endocardial atrial recordings of AFib, sinus rhythm, atrial flutter, and supraventricular tachycardia were collected using a catheter with orthogonally placed electrodes, and the direction of each activation was calculated using methods previously described by our laboratory. Each recording was divided into segments containing 100 activations, and the spatial precision for each segment was calculated in three dimensions, as well as in each of the three two-dimensional (2-D) planes. The three-dimensional (3-D) spatial precision for 1161 segments of AFib in 11 recordings ranged from 0.09-0.85 (mean=0.45), whereas the spatial precision for 138 segments of regular rhythms in 28 recordings was ⩾0.91 in all but four instances. The 2-D spatial precision values overlapped for all rhythms. The results indicate that 3-D spatial precision of local activation direction is a useful discriminator of AFib     

Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation

A new method for QRST cancellation is presented for the analysis of atrial fibrillation in the surface electrocardiogram (ECG). The method is based on a spatiotemporal signal model which accounts for dynamic changes in QRS morphology caused, e.g., by variations in the electrical axis of the heart. Using simulated atrial fibrillation signals added to normal ECGs, the results show that the spatiotemporal method performs considerably better than does straightforward average beat subtraction (ABS). In comparison to the ABS method, the average QRST-related error was reduced to 58 percent. The results obtained from ECGs with atrial fibrillation agreed very well with those from simulated fibrillation signals.     

Characterization of surface states in HCl-grown oxides using MOS transient currents

A fast transient current (TC) technique has been developed for the characterization of majority carrier charge emission from surface states using MOS capacitors excited by a voltage step-function. This technique, with appropriate choice of initial and final biasing conditions, allows a rapid determination of the density of surface states (N_ss) and their capture cross section values (σ_n) in preselected regions of band gap using suitable temperature ambients. A low temperature (113°K) was used for regions close to the bottom of conduction band and room temperature and moderately low temperatures were used for the mid-gap region. Results of transient current measurements were compared with those obtained from thermally stimulated current and low frequency C-V measurements. The MOS devices were fabricated using [100] oriented n-type (6–8 Ω-cm) silicon on n⁺ substrates with HCl added to the oxidizing ambient. The detectability limit of the TC technique has been found to be approximately 1 × 10¹⁰ cm^?2 eV^?1 for the device area used.     

A technique for measurement of the extent of spatial organizationof atrial activation during atrial fibrillation in the intact humanheart

Atrial fibrillation (AF) is a common clinical problem, associated with considerable morbidity and motility, for which effective management strategies have yet to be devised. The absence of objective measures to guide selection of antiarrhythmic drug therapy for maintenance of sinus rhythm leaves only clinical endpoints (either beneficial or detrimental) for assessment of drug action, with occasional catastrophic consequences. As part of an attempt to provide an objective framework for the assessment of antiarrhythmic drug action on the electrophysiologic determinants of atrial fibrillation, the authors have developed a measure of the spatial organization of atrial activation processes during atrial fibrillation. By recording activation sequences at multiple equally spaced locations on the endocardial surface of the atrial during atrial fibrillation in humans and determining the degree of correlation between these activation sequences as a function of distance, the authors have been able to construct spatial correlation functions for atrial activation. They have found that atrial activation remains well-correlated, independent of distance during normal sinus rhythm and atrial flutter. During atrial fibrillation, correlation decays monotonically with distance and the space-constant for this decay may be used to describe the relative spatial organization of atrial fibrillation. The authors provide examples of the impact of antiarrhythmic agents on the space-constant and suggest that assessment of the relative spatial organization of atrial activation using this methodology may potentially provide an objective framework to guide therapy in patients with AF