A high-temporal resolution algorithm for quantifying organization during atrial fibrillation

Atrial fibrillation (AF) has been described as a "random" or "chaotic" rhythm. Evidence suggests that AF may have transient episodes of temporal and spatial organization. We introduce a new algorithm that quantifies AF organization by the mean-squared error (MSE) in the linear prediction between two cardiac electrograms. This algorithm calculates organization at a finer temporal resolution. (approximately 300 ms) than previously published algorithms. Using canine atrial epicardial mapping data, we verified that the MSE algorithm showed nonfibrillatory rhythms to be significantly more organized than fibrillatory rhythms (p < .00001). Further, we compared the sensitivity of MSE to that of two previously published algorithms by analyzing AF with simulated noise and AF manipulated with vagal stimulation or by adenosine administration to alter the character of the AF. MSE performed favorably in the presence of noise. While all three algorithms distinguished between low and high vagal AF, MSE was the most sensitive in its discrimination. Only MSE could distinguish baseline AF from AF with adenosine. We conclude that our algorithm can distinguish different levels of organization during AF with a greater temporal resolution and sensitivity than previously described algorithms. This algorithm could lead to new ways of analyzing and understanding AF as well as improved techniques in AF therapy.     

Frequency domain least-mean-square algorithm

Frequency domain adaptive filtering can be performed by Fourier transforming the input-signal vector and weighting the contents of each frequency bin. By reducing the eigenvalue spread of the data autocorrelation matrix, frequency domain filtering promises great improvements in covergence rate over the conventional time-domain adaptive filtering.     

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.     

Frequency domain set membership fast normalised LMS adaptive algorithm

The concept of set membership (SM) adaptive filtering is extended to the frequency domain and a novel frequency domain SM algorithm is derived. Simulations show that the new SM algorithm has a much improved convergence rate over the conventional fast normalised least mean square (FNLMS) algorithm with identical misadjustment performance. Moreover, the SM algorithm has the same order of computational complexity as the FNLMS algorithm.     

A simple time domain algorithm for the detection of ventricular fibrillation in electrocardiogram

Ventricular fibrillation (VF) is the most serious variety of arrhythmia which requires quick and accurate detection to save lives. In this paper, we propose a new time domain algorithm, called threshold crossing sample count (TCSC), which is an improved version of the threshold crossing interval (TCI) algorithm for VF detection. The algorithm is based on an important feature of the VF signal which relies on the random behavior of the electrical heart vector. By two simple operations: comparison and count, the technique calculates an effective measure which is used to separate life-threatening VF from other heart rhythms. For assessment of the performance of the algorithm, the method is applied on the complete MIT-BIH arrhythmia and CU databases, and a promising good performance is observed. Seven other classical and new VF detection algorithms, including TCI, have been simulated and comparative performance results in terms of different quality parameters are presented. The TCSC algorithm yields the highest value of the area under the receiver operating characteristic curve (AUC). The new algorithm shows strong potential to be applied in clinical applications for faster and accurate detection of VF.     

Frequency domain equalization for single-carrier broadband wirelesssystems

Broadband wireless access systems deployed in residential and business environments are likely to face hostile radio propagation environments, with multipath delay spread extending over tens or hundreds of bit intervals. Orthogonal frequency-division multiplex (OFDM) is a recognized multicarrier solution to combat the effects of such multipath conditions. This article surveys frequency domain equalization (FDE) applied to single-carrier (SC) modulation solutions. SC radio modems with frequency domain equalization have similar performance, efficiency, and low signal processing complexity advantages as OFDM, and in addition are less sensitive than OFDM to RF impairments such as power amplifier nonlinearities. We discuss similarities and differences of SC and OFDM systems and coexistence possibilities, and present examples of SC-FDE performance capabilities     

Frequency domain computations for nonlinear steady-state solutions

Steady-state analysis and Fourier analysis play a major role in linear signal processing. In response to a bounded input, a steady-state solution exists if all the poles of the discrete-time linear system are inside the unit circle. Despite the fact that there is no principle of superposition for nonlinear systems, under appropriate sufficient conditions (including all poles inside the unit circle for the linear part of the nonlinear system), there is a bounded solution for all time in response to a bounded input for all time for a time-varying nonlinear difference equation. All solutions that start sufficiently close to this unique solution converge to it as time goes to infinity. This steady-state solution can be computed by applying Fourier and inverse Fourier transforms to each step in a Picard process. In this paper, we develop an algorithm to compute (approximate) steady-state solutions for discrete-time, nonlinear difference equations by employing fast Fourier transforms and inverse fast Fourier transforms at each step of the iterative process. Simulations are provided to illustrate our algorithm     

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.     

Constrained registration for motion compensation in atrial fibrillation ablation procedures

Fluoroscopic overlay images rendered from preoperative volumetric data can provide additional anatomical details to guide physicians during catheter ablation procedures for treatment of atrial fibrillation (AFib). As these overlay images are often compromised by cardiac and respiratory motion, motion compensation methods are needed to keep the overlay images in sync with the fluoroscopic images. So far, these approaches have either required simultaneous biplane imaging for 3-D motion compensation, or in case of monoplane X-ray imaging, provided only a limited 2-D functionality. To overcome the downsides of the previously suggested methods, we propose an approach that facilitates a full 3-D motion compensation even if only monoplane X-ray images are available. To this end, we use a training phase that employs a biplane sequence to establish a patient specific motion model. Afterwards, a constrained model-based 2-D/3-D registration method is used to track a circumferential mapping catheter. This device is commonly used for AFib catheter ablation procedures. Based on the experiments on real patient data, we found that our constrained monoplane 2-D/3-D registration outperformed the unconstrained counterpart and yielded an average 2-D tracking error of 0.6 mm and an average 3-D tracking error of 1.6 mm. The unconstrained 2-D/3-D registration technique yielded a similar 2-D performance, but the 3-D tracking error increased to 3.2 mm mostly due to wrongly estimated 3-D motion components in X-ray view direction. Compared to the conventional 2-D monoplane method, the proposed method provides a more seamless workflow by removing the need for catheter model re-initialization otherwise required when the C-arm view orientation changes. In addition, the proposed method can be straightforwardly combined with the previously introduced biplane motion compensation technique to obtain a good trade-off between accuracy and radiation dose reduction.     

Frequency domain multiplexing for parallel acquisition of MR images

A frequency domain multiplexing (FDM) technique is described for parallel acquisition of magnetic resonance images. Two signals from different RF coils encoded with different frequencies were combined to feed into a high-speed ADC. The multiplexed signal is then decoded by a commercial multi-carrier digital receiver. Experimentation found no phase shift, no SNR loss and essentially no crosstalk in the proposed FDM method. It is expected that the FDM technique, with the development of commercially available digital receivers, may be valuable and cost-effective in the design of a parallel MRI receiver system.     

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.     

Frequency domain detectors for ultra-wideband communications in short-range systems

In this paper, we propose an original detection scheme for high rate short-range impulse radio ultra-wideband systems. The proposed receiver relies on both the introduction of the cyclic prefix at the transmitter and the use of a frequency domain multiuser detector at the receiver. Zero forcing (ZF) and minimum mean square error (MMSE) detection strategies have been investigated and compared with the classical RAKE, considering a scenario where several mobile terminals communicate with a base station in an indoor environment characterized by severe multipath propagation. The results show that the MMSE receiver achieves the best performance, irrespective of the number of active terminals, both in the uplink and in the downlink communications. Hence, the proposed approach is well suited in indoor wireless environments where the multipath propagation tends to increase the effects of both the inter-path and the inter-user interference.     

Frequency domain decision feedback equalizer for time-reversal space-time block coding

In this paper,a frequency domain decision feedback equalizer is proposed for single carrier transmission with time-reversal space-time block coding (TR-STBC).It is shown that the diagonal decision feed...     

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.     

Frequency domain postfiltering for multiband excited linearpredictive coding of speech

A frequency domain postfilter for multiband excited linear predictive (MBELP) coders is proposed. It is based on the principle of multiplying the signal band magnitudes by the postfilter magnitudes obtained by sampling the postfilter response at the pitch harmonics. This approach offers two major advantages: first, the signal energies before and after postfiltering can be equalised by simply rescaling the signal band magnitudes; and secondly, the phase information will be retained owing to only the magnitude spectra being modified. A fast method is given for sampling the postfilter magnitude spectrum characterised by line spectral pair (LSP) parameters     

Frequency domain pilot multiplexing technique for channel estimation of SC-FDE

A frequency domain pilot multiplexing technique for channel estimation of single-carrier frequency domain equalisation (SC-FDE) is proposed. The proposed scheme selects pilot positions to minimise the pre-imposed distortion caused by the loss of useful data tones. The corresponding receiver structure is also presented, where the pilot positions are blindly detected and the distorted data symbols are iteratively reconstructed. Simulation results show that the proposed system approaches the lower bound of SC-FDE.     

Fast spectral domain algorithm for rapid solution of integralequations

A fast spectral domain algorithm is presented for rapid solution of planar surface integral equations. The method of moments coupling integral matrix is formulated in the spectral domain but not explicitly calculated. Thus, in conjunction with an iterative equation solver, the pertinent matrix/vector products are evaluated with complexity O(n) where n is the number of unknowns. Validation and timing results are presented for an array analysis approach using a hybrid finite element (FE)-boundary integral implementation     

A fast multilevel domain decomposition algorithm for radar imaging

A novel algorithm for radar imaging is presented. The method comprises two steps. First, a decomposition of the radar data domain into subdomains and computation of pertinent low resolution images. Second, interpolation, phase correction and aggregation of the low resolution images into the final high resolution one. A multilevel algorithm is formulated via a recursive application of the domain decomposition and image aggregation steps. The computational cost of the proposed algorithm is comparable to that of the fast Fourier transform (FFT) based techniques while it appears to be considerably more flexible than the latter     

光正交频分复用系统时域均衡算法研究

提出了时域DD-LMS均衡法在O-OFDM系统中的应用.理论分析了DD-LMS均衡原理,实验验证了在直接检测O-OFDM系统中用DD-LMS均衡法比用LS均衡法的系统的平均功率代价降低了1dB;在相同接收功率下,使用DD-LMS均衡方法的系统误码率比使用LS均衡系统误码率降低很多,相应信号星座图也较收敛.