Spectrotemporal Mapping Research Articles

Acquisition of English Phonology: Spectro-Temporal Mapping of English Mid Vowels in Pakistan

Acquisition of English Phonology: Spectro-Temporal Mapping of English Mid Vowels in Pakistan

Atrial activation during sinus rhythm in patients with rheumatic and non-rheumatic paroxysmal atrial fibrillation. Frequency-domain analysis using signal-averaged electrocardiography.

Using P-wave signal-averaged electrocardiography, we assessed the patterns of atrial electrical activation in patients with idiopathic atrial fibrillation as compared with patterns in patients with atrial fibrillation associated with structural heart disease. Eighty patients with recurrent paroxysmal atrial fibrillation were divided into 3 groups as follows: group I - 40 patients with atrial fibrillation associated with non-rheumatic heart disease; group II - 25 patients with rheumatic atrial fibrillation; and group III - 15 patients with idiopathic atrial fibrillation. All patients underwent P-wave signal-averaged electrocardiography for frequency-domain analysis using spectrotemporal mapping and statistical techniques for detecting and quantifying intraatrial conduction disturbances. We observed an important fragmentation in atrial electrical conduction in 27% of the patients in group I, 64% of the patients in group II, and 67% of the patients in group III (p=0.003). Idiopathic atrial fibrillation has important intraatrial conduction disturbances. These alterations are similar to those observed in individuals with rheumatic atrial fibrillation, suggesting the existence of some degree of structural involvement of the atrial myocardium that cannot be detected with conventional electrocardiography and echocardiography.

Failure of spectro-temporal mapping to detect ventricular late potentials in dogs

Abstract Objective To determine whether ventricular late potentials (LP) identified by time-domain analysis (TDA) of the signal-averaged ECG could be identified by three-dimensional frequency-domain analysis (FDA). Animals 11 dogs (9 of which subsequently died suddenly) with ventricular tachyarrhythmias (10 with ventricular tachycardia) and abnormal TDA of the signal-averaged ECG. Procedure Signal-averaged ECG that were abnormal when analyzed in the time domain subsequently were processed further in the frequency domain. Correlation ratios were calculated, and spectro-temporal maps were plotted, which were then compared with control data. Results Three-dimensional FDA did not detect LP. Conclusions and Clinical Relevance LP may be detectable by TDA of the signal-averaged ECG and may be a specific marker for VT and sudden death in some dogs. However, FDA by use of the method applied in this study is invalid. (Am J Vet Res 1999;60: 396-401)

Signal-averaged electrocardiograms in normal Doberman pinschers.

Signal-averaged electrocardiograms (SAECGs) were performed on nonsedated normal dogs in left-lateral recumbency. Following signal averaging, both time-domain and 3-dimensional frequency-domain analyses were performed. For time-domain analysis, the high-frequency QRS (HFQRS) duration, duration of the terminal QRS complex less than 40 microV (LAS40), and root mean square (RMS) voltages (microV) of the terminal 40 milliseconds (RMS40) and 30 milliseconds of the QRS complex were calculated. For frequency-domain analysis, correlation ratios were calculated for 30-, 40-, 50-, and 60-millisecond segment lengths begun 10, 15, or 20 milliseconds before the end of the QRS complex. Spectro-temporal mapping was also performed. All of the parameters of the SAECGs analyzed in the time domain were associated with each other. LAS40 and RMS voltages regressed significantly (P < .0000) on the HFQRS duration. Ninety-five percent of the HFQRSs were 55-75 milliseconds, 95% of the LAS40s were 9-26 milliseconds, and 95% of the RMS40 voltages were 177-444 microV. None of the SAECGs contained evidence of ventricular late potentials. Spectro-temporal maps were similar in each dog when the same segment lengths and starting points were compared. No evidence of ventricular late potentials was observed. Correlation ratios were lower when windowed segments included 15 or 20 milliseconds (versus 10 milliseconds) of the terminal QRS complex. When only 10 milliseconds of the terminal QRS complex were included in windowed segments, the mean correlation ratios for 30- and 40-millisecond segment lengths were > 0.8 and > 0.61 in 67% of all analyses, respectively.

Spectro-temporal mapping of the surface electrocardiogram in clinically normal dogs

Abstract Objectives To establish data for selected variables of the signal-averaged ECG and determine whether sedation affects segment lengths and points within the terminal QRS complex where windows began. Sample Population Overtly healthy dogs with no detected abnormalities. Procedure Signal-averaged ECG (600 beats) were obtained from dogs in left-lateral recumbency, using X, Y, and Z leads with 26-gauge subdermal platinum electrodes. Frequency-domain analyses were performed by fast Fourier transform (FFT), using a postprocessing computer software package. Analyses were extracted from 30-, 40-, and 50-millisecond windowed (Blackman-Harris) segments of the terminal 10 or 20 milliseconds of the QRS complex and ST segment. Correlation ratios were calculated by cross-correlation of frequency spectra of each FFT in the range of 40 to 200 Hz. The reference spectrum was the last FFT (nearest the T wave). Spectro-temporal maps were plotted for each analysis. Results Noise levels were &lt; 1 μV. Sedation resulted in less noise and slower heart rate, but did not affect results. Correlation ratios were not different among 30-, 40-, and 50-millisecond segments, but were lower when 20 (vs 10) milliseconds of the terminal QRS was included. Spectro-temporal maps were similar in all subjects. Conclusions Use of sedation facilitated the procedure without affecting results. Segment lengths of 40 and 50 milliseconds, beginning 10 milliseconds prior to the end of the QRS complex and analyzed in the range of 40 to 200 Hz, yielded correlation ratios &gt; 67%, 95% of the time. Clinical Relevance Spectro-temporal mapping may identify dogs with ventricular late potentials (high-frequency signals commonly associated with myocardial fibrosis) that may be at increased risk of sudden death. (Am J Vet Res 1997;58:211–217)

Functional Late Potential Analysis With Exercise Testing to Identify Patients Prone to Ventricular Tachycardia After Myocardial Infarction

Objective: Exercise induced ischemia or heart rate acceleration may unmask late potentials or provoke functional changes, which might be important factors to improve the low positive predictive value of late potential analysis at rest for postinfarction risk stratification. However, methodological refinements are required to detect late potentials with exercise.Methods: We, therefore, investigated the surface‐electrocardiogram in 100 patients after myocardial infarction (50 with sustained ventricular tachycardia [group I], 50 patients without ventricular arrhythmias [group II], and in 15 normals before and immediately after bicycle exercise test using Spectrotemporal Mapping (STM) with fast Fourier transform (FFT) and Simson method and introduced selective signal averaging.Results: In group I, 30 out of 50 patients showed late potentials at rest, after selective signal averaging also recognizable immediately after exercise in all of these patients, however, with a time‐shift of 18 ± 13 ms into the ST‐segment. Twelve out of 50 patients of group I with only transient late potentials tended to have inducible and recurrent ventricular tachycardia with a shorter cycle length. In group II, 4 out of 50 patients had late potentials at rest and 2 out of 46 patients developed them during exercise. Transient pathological Simson method was associated with transmural ischemia.Conclusions: Thus, detection of the effects of exercise on late potential analysis is possible with selective signal averaging immediately after exercise. Exercise unmasks late potentials not detectable at rest by their time‐shift into the ST‐segment. Using this method, patients that would have been lost with conventional late potential analysis, could be identified.

COMBINED TIME AND FREQUENCY DOMAIN ANALYSIS OF THE SIGNAL-AVERAGED ELECTROCARDIOGRAM IN TOP-LEVEL ATHLETES WITH VENTRICULAR ARRHYTHMIAS141

Signal averaged electrocardiogram (SAECG) is a useful non invasive tool for sudden death risk stratification in top-level athletes (A)with complex ventricular arrhythmias (CVA). There is no agreemente regarding the choice of the best criteria to apply. Two groups (GR) of A were studied: GR1 including 24 A with CVA without heart disease and GR2 formed by 81 apparently healthy A without CVA. All A underwent SAECG with the noise ≤ 0.3 μV. 25 and 40-250 Hz filters were used. Spectro-Temporal Mapping (STM)has been built for each X, Y and Z lead. SAECG was positive if:a)QRSD>114 ms, LAS 40>38 ms and RMS<20μV at 40-250 Hz;b)Normality factor ≤ 30% in any lead at STM;c)positivity of a)&b) criteria. The prevalence of an abnormal SAECG was: 37.5% in GR1 vs 6% in GR2 with method a) (p=0.000);20.8% vs 2.5% with b)(p=0.007) and 12.5% in GR1 vs 0% in GR2 with c) (p=0.011). In conclusion, A with CVA have a significant higher prevalence of ventricular late potentials than non-CVA A. The real meaning of an abnormal SAECG in A with CVA is still uncertain and long-term follow-up studies and inducibility tests are needed. Combined time and frequency domain analysis (method c) is likely to be the best one to apply because is able to differentiate A with from those without CVA, allowing the lowest rate of false positive results.

Late potentials and spectro-temporal mapping for predict electric instability of the myocardium

Late potentials and spectro-temporal mapping for predict electric instability of the myocardium

Time-frequency structure of the high-resolution ECG

This study considers the problem of representing high-resolution ECG (HRECG) signals in the time-frequency plane using spectrotemporal mapping (STM). High-resolution ECG signal components overlap in both time and frequency. The central issue with STM techniques is whether sufficient time-frequency resolution exists to discriminate normal and abnormal QRS signals. The trade-off between signal resolution in time and in frequency must be made without a priori knowledge of the HRECG's time-frequency structure. A simulation experiment was performed to examine the time-frequency distribution of normal, abnormal low-level (late potentials), and bundle branch block components of the QRS. Results suggest that discrimination of these signals with STM is problematic. Signals and noise within the HRECG ensemble can, however, be easily distinguished. This observation forms the basis of a new optimally filtered ensemble averaging technique for signal-to-noise ratio enhancement.

Time-domain and frequency-domain analyses of the signal-averaged ECG in patients with sustained ventricular tachyarrhythmia and nonischemic heart diseases

Signal-averaged electrocardiogram (ECG) variables were analyzed in 81 patients with ventricular tachyarrhythmia and nonischemic heart disease using the ART LVP 101 EPX system (Austin, TX): 15 ventricular tachycardia patients with arrhythmogenic right ventricular dysplasia (ARVD), 7 ventricular tachycardia patients with dilated cardiomyopathy, 25 patients with “idiopathic” verapamil-sensitive left ventricular tachycardia, 24 patients with “idiopathic” right ventricular tachycardia, and 10 “idiopathic” ventricular fibrillation (IVF) patients with rbbb pattern and ST-segment elevation in the precordial leads. Data from 52 normal control subjects were also analyzed. The first study was to test the hypothesis of any difference in signal-averaged ECG indices between patients with ARVD and patients with dilated cardiomyopathy. Longer filtered QRS duration and T40 and higher amplitude of the terminal filtered QRS complex outside the end of the standard QRS complex (log V-outside) were noted in patients with ARVD (filtered QRS duration, 172 vs 144 ms, P < .05; T40, 94 vs 62 ms, P < .05; log V-outside, 1.48 vs 0.56, P < .01). Endocardial mapping showed noticeable extension of fractionated electrograms in the right ventricle and longer duration of fractionated intracardiac electrograms in patients with ARVD, which might explain the difference in signal-averaged ECG indices between these two diseases. The second study was to test the hypothesis of and the variables that can suggest the arrhythmogenic substrate in patients with idiopathic ventricular tachycardia. Signal-averaged ECG indices in time-domain and frequency-domain (fast Fourier transform method: area ratio, spectrotemporal mapping) analyses did not indicate any differences between patients with idiopathic ventricular tachycardia and normal control subjects. The third study was to test the hypothesis of any indices that suggest the arrhythmogenic substrate in patients with IVF. Time-domain analysis showed some difference between patients with IVF and normal control subjects (but not statistically significant because of a small number of patients with IVF).

The signal-averaged ECG: time-domain analysis.

During the past decade, the high-resolution electrocardiogram as a non-invasive technique for the detection of ventricular late potentials has developed from an experimental method into a routinely applied non-invasive method for risk stratification of patients after myocardial infarction. Meanwhile, several approaches have been developed for the detection of ventricular late potentials including time-domain analysis, frequency-domain analysis and spectrotemporal mapping. Clinical applications are no longer limited to patients after myocardial infarction, but cover a wider spectrum of different cardiac diseases. This review focuses on some methodological aspects as well as on the results and current clinical applications of the analysis of the signal-averaged ECG in the time domain.

Influence of phase and duration of analyzed segment to the results of spectro-temporal mapping

Influence of phase and duration of analyzed segment to the results of spectro-temporal mapping

第2回 体表心臓微小電位研究会 Spectro-temporal mappingによる心筋梗塞後心室頻拍の予知

第2回 体表心臓微小電位研究会 Spectro-temporal mappingによる心筋梗塞後心室頻拍の予知

Ventricular Late Potentials in Myotonic Dystrophy

To determine the prevalence of ventricular late potentials, as determined by signal-averaged electrocardiography, in patients with myotonic dystrophy. Cross sectional, with blinded analysis of all electrocardiographic data. Outpatient departments of a Veterans Affairs medical center and a tertiary care private hospital. Twenty-four patients with myotonic dystrophy. Patients were excluded from the study if they had either a history suggestive of significant ventricular arrhythmias or electrocardiographic evidence of a bundle-branch block. Two comparison groups were also formed; one group included 44 healthy employees at the tertiary hospital and the other, 30 cardiac patients with inducible ventricular tachycardia. A time-domain analysis of the signal-averaged electrocardiograms showed that 75% of patients with myotonic dystrophy met one criterion for the presence of late potentials, 67% met two criteria, and 29% met all three criteria. Spectrotemporal mapping in these patients showed markedly abnormal spectral peaks with a mean factor of normality that was significantly lower than that of the normal volunteers; the frequency of electrocardiographic abnormalities approached that seen in patients with known ventricular tachycardia. The presence of late potentials correlated directly with the length of the PR interval and inversely with left ventricular fractional shortening. In our study, the prevalence of late potentials on signal-averaged electrocardiography in patients with myotonic dystrophy approached that seen in cardiac patients with inducible ventricular tachycardia. It is possible that ventricular arrhythmias play a role in the occurrence of sudden death in some patients with myotonic dystrophy.

Spectro-temporal mapping for risk of sustained ventricular arrhythmias: Quantitative analysis in post-MI patients

Spectro-temporal mapping for risk of sustained ventricular arrhythmias: Quantitative analysis in post-MI patients

Frequency analysis of the electrocardiogram with maximum entropy method for identification of patients with sustained ventricular tachycardia

Late potentials in the terminal phase of the QRS-complex during sinus rhythm have been proposed to identify a subgroup of patients with myocardial infarction at risk of ventricular tachycardia (VT). Frequency analysis of the ECG with Fourier transform (FFT) has been applied for detection of these microvolt level signals, but is limited by poor frequency resolution of short data segments and spectral leakage. We therefore developed frequency analysis using the maximum entropy method (MEM) based on an autoregressive (AR) model. Orthogonal electrocardiograms were recorded from the body surface of patients with and without VT, and healthy persons after low noise, high-gain amplification. Multiple 40 ms segments (time intervals 2 ms, AR-parameters tapered) were analyzed (spectrotemporal mapping): low-frequency components were eliminated by building difference spectra with optimal high order and fixed low order. The MEM-spectra revealed high frequency components (40-200 Hz) in the terminal phase of the QRS-complex and in the ST-section in 26/38 patients with VT, but only in 2/20 without VT and in 1/20 healthy persons (p less than 0.05). Unlike FFT, MEM allowed localization of late potentials by the analysis of short data segments. Thus, MEM offers promise for noninvasive identification of patients with sustained VT after myocardial infarction and detailed analysis of late potentials.

Top-resolution frequency analysis of electrocardiogram with adaptive frequency determination. Identification of late potentials in patients with coronary artery disease.

Frequency analysis of the electrocardiogram with Fourier transform is a sensitive method of detecting late potentials. However, information about localization of late potentials is lost, frequency resolution is poor, and window functions have to be applied. We therefore analyzed multiple segments (25 msec long) of the surface electrocardiogram ("spectrotemporal mapping") with adaptive frequency determination (AFD), an autoregressive algorithm that is characterized by high-frequency resolution in very short segments without the use of window functions. Results were compared with those from Fourier transform and the Simson method. We studied 38 patients after myocardial infarction (MI) with sustained ventricular tachycardia (VT), 21 patients after MI without VT, and 18 healthy subjects. Frequency peaks could be clearly differentiated until a minimal interval of 6 Hz; with fast Fourier transform (Blackman Harris window) in a much longer segment (80 msec), the spectral peaks merged into one another at an interval of about 30 Hz. AFD revealed high-frequency components as narrow peaks in the range of 40-160 Hz in 28 of 38 patients (74%) after MI with VT. Because of the short segment size, exact localization of late potentials was possible; in most of the patients, the peaks occurred in segments inside the QRS complex and ended 20 +/- 10 msec after termination of the QRS complex. In patients after MI without VT, only four of 21 patients (19%) had spectral peaks in segments after the end of the QRS complex; however, 13 of 21 patients demonstrated microvolt potentials in segments within the QRS complex. These potentials did not extend beyond the end of normal ventricular activation. Only two of 18 healthy subjects showed abnormal AFD results. Patients with bundle branch block did not need to be excluded. AFD allowed good differentiation between late potentials and noise by a characteristic pattern of the spectral peaks. For the Simson method, patients with bundle branch block had to be excluded, and overall sensitivity was 42%. In five cases, the cause of failure of the Simson method could be identified as incorrect determination of the QRS limits due to noise. Thus, AFD is a promising method for detailed analysis of late potentials; it combines the advantages of frequency analysis (good differentiation between signal and noise and high-pass filters not necessary) and time domain analysis (localization of late potentials).

Spectrotemporal analysis of ventricular late potentials

The authors introduce a new technique for the analysis of ventricular late potentials: spectrotemporal mapping. Spectrotemporal mapping displays a signal in both the time and frequency domains simultaneously, overcoming some of the limitations of single domain analysis. Spectrotemporal analysis of late potentials was developed from a critique of classical spectral analysis methods. Several examples of spectrotemporal analysis of signal-averaged ECG wave-forms are presented. These include cases in which spectrotemporal mapping was able to represent late potentials that were not seen after conventional time-domain processing. Spectrotemporal mapping reveals that ventricular late potentials have a time-varying energy spectrum, which theoretically would preclude the use of classical Fourier analysis techniques. Both the vector magnitude and Fourier transformations are a reduced representation of the information available in the signal average. Spectrotemporal mapping combines time and frequency information in a way that is compatible with the basic statistical structure of late potentials.

Three-dimensional spectrotemporal mapping of the signal-averaged ECG identifies patients with ventricular tachycardia despite the presence of pundle branch block

Three-dimensional spectrotemporal mapping of the signal-averaged ECG identifies patients with ventricular tachycardia despite the presence of pundle branch block