Signal Quality Assessment of a Novel ECG Electrode for Motion Artifact Reduction.

BACKGROUND: The presence of noise is problematic in the analysis and interpretation of the ECG, especially in ambulatory monitoring. Restricting the analysis to high-quality signal segments only comes with the risk of excluding significant arrhythmia episodes. Therefore, the development of novel electrode technology, robust to noise, continues to be warranted. METHODS: The signal quality of a novel wet ECG electrode (Piotrode) is assessed and compared to a commercially available, commonly used electrode (Ambu). The assessment involves indices of QRS detection and atrial fibrillation detection performance, as well as signal quality indices (ensemble standard deviation and time-frequency repeatability), computed from ECGs recorded simultaneously from 20 healthy subjects performing everyday activities. RESULTS: The QRS detection performance using the Piotrode was considerably better than when using the Ambu, especially for running but also for lighter activities. The two signal quality indices demonstrated similar trends: the gap in quality became increasingly larger as the subjects became increasingly more active. CONCLUSIONS: The novel wet ECG electrode produces signals with less motion artifacts, thereby offering the potential to reduce the review burden, and accordingly the cost, associated with ambulatory monitoring.

Modeling and quality assessment of nystagmus eye movements recorded using an eye-tracker.

Mathematical modeling of nystagmus oscillations is a technique with applications in diagnostics, treatment evaluation, and acuity testing. Modeling is a powerful tool for the analysis of nystagmus oscillations but quality assessment of the input data is needed in order to avoid misinterpretation of the modeling results. In this work, we propose a signal quality metric for nystagmus waveforms, the normalized segment error (NSE). The NSE is based on the energy in the error signal between the observed oscillations and a reconstruction from a harmonic sinusoidal model called the normalized waveform model (NWM). A threshold for discrimination between nystagmus oscillations and disturbances is estimated using simulated signals and receiver operator characteristics (ROC). The ROC is optimized to find noisy segments and abrupt waveform and frequency changes in the simulated data that disturb the modeling. The discrimination threshold, 𝜖, obtained from the ROC analysis, is applied to real recordings of nystagmus data in order to determine whether a segment is of high quality or not. The NWM parameters from both the simulated dataset and the nystagmus recordings are analyzed for the two classes suggested by the threshold. The optimized 𝜖 yielded a true-positive rate and a false-positive rate of 0.97 and 0.07, respectively, for the simulated data. The results from the NWM parameter analysis show that they are consistent with the known values of the simulated signals, and that the method estimates similar model parameters when performing analysis of repeated recordings from one subject.

A robust method for calibration of eye tracking data recorded during nystagmus.

Eye tracking is a useful tool when studying the oscillatory eye movements associated with nystagmus. However, this oscillatory nature of nystagmus is problematic during calibration since it introduces uncertainty about where the person is actually looking. This renders comparisons between separate recordings unreliable. Still, the influence of the calibration protocol on eye movement data from people with nystagmus has not been thoroughly investigated. In this work, we propose a calibration method using Procrustes analysis in combination with an outlier correction algorithm, which is based on a model of the calibration data and on the geometry of the experimental setup. The proposed method is compared to previously used calibration polynomials in terms of accuracy, calibration plane distortion and waveform robustness. Six recordings of calibration data, validation data and optokinetic nystagmus data from people with nystagmus and seven recordings from a control group were included in the study. Fixation errors during the recording of calibration data from the healthy participants were introduced, simulating fixation errors caused by the oscillatory movements found in nystagmus data. The outlier correction algorithm improved the accuracy for all tested calibration methods. The accuracy and calibration plane distortion performance of the Procrustes analysis calibration method were similar to the top performing mapping functions for the simulated fixation errors. The performance in terms of waveform robustness was superior for the Procrustes analysis calibration compared to the other calibration methods. The overall performance of the Procrustes calibration methods was best for the datasets containing errors during the calibration.

Safe automatic one-lead electrocardiogram analysis in screening for atrial fibrillation.

AIMS: Screening for atrial fibrillation (AF) using intermittent electrocardiogram (ECG) recordings can identify individuals at risk of AF-related morbidity in particular stroke. We aimed to validate the performance of an AF screening algorithm compared with manual ECG analysis by specially trained nurses and physicians (gold standard) in 30 s intermittent one-lead ECG recordings. METHODS AND RESULTS: The STROKESTOP study is a mass-screening study for AF using intermittent ECG recordings. All individuals in the study without known AF registered a 30-s ECG recording in Lead I two times daily for 2 weeks, and all ECGs were manually interpreted. A computerized algorithm was used to analyse 80 149 ECG recordings in 3209 individuals. The computerized algorithm annotated 87.1% (n = 69 789) of the recordings as sinus rhythm/minor rhythm disturbances. The manual interpretation (gold standard) was that 69 758 ECGs were normal, making the negative predictive value of the algorithm 99.9%. The number of ECGs requiring manual interpretation in order to find one pathological ECG was reduced from 288 to 35. Atrial fibrillation was diagnosed in 84 patients by manual interpretation, in all of whom the algorithm indicated pathology. On an ECG level, 278 ECGs were manually interpreted as AF, and of these the algorithm annotated 272 ECGs as pathological (sensitivity 97.8%). CONCLUSION: Automatic ECG screening using a computerized algorithm safely identifies normal ECGs in Lead I and reduces the need for manual evaluation of individual ECGs with >85% with 100% sensitivity on an individual basis.

One algorithm to rule them all? An evaluation and discussion of ten eye movement event-detection algorithms.

Almost all eye-movement researchers use algorithms to parse raw data and detect distinct types of eye movement events, such as fixations, saccades, and pursuit, and then base their results on these. Surprisingly, these algorithms are rarely evaluated. We evaluated the classifications of ten eye-movement event detection algorithms, on data from an SMI HiSpeed 1250 system, and compared them to manual ratings of two human experts. The evaluation focused on fixations, saccades, and post-saccadic oscillations. The evaluation used both event duration parameters, and sample-by-sample comparisons to rank the algorithms. The resulting event durations varied substantially as a function of what algorithm was used. This evaluation differed from previous evaluations by considering a relatively large set of algorithms, multiple events, and data from both static and dynamic stimuli. The main conclusion is that current detectors of only fixations and saccades work reasonably well for static stimuli, but barely better than chance for dynamic stimuli. Differing results across evaluation methods make it difficult to select one winner for fixation detection. For saccade detection, however, the algorithm by Larsson, Nyström and Stridh (IEEE Transaction on Biomedical Engineering, 60(9):2484-2493,2013) outperforms all algorithms in data from both static and dynamic stimuli. The data also show how improperly selected algorithms applied to dynamic data misestimate fixation and saccade properties.

Smooth pursuit detection in binocular eye-tracking data with automatic video-based performance evaluation.

An increasing number of researchers record binocular eye-tracking signals from participants viewing moving stimuli, but the majority of event-detection algorithms are monocular and do not consider smooth pursuit movements. The purposes of the present study are to develop an algorithm that discriminates between fixations and smooth pursuit movements in binocular eye-tracking signals and to evaluate its performance using an automated video-based strategy. The proposed algorithm uses a clustering approach that takes both spatial and temporal aspects of the binocular eye-tracking signal into account, and is evaluated using a novel video-based evaluation strategy based on automatically detected moving objects in the video stimuli. The binocular algorithm detects 98% of fixations in image stimuli compared to 95% when only one eye is used, while for video stimuli, both the binocular and monocular algorithms detect around 40% of smooth pursuit movements. The present article shows that using binocular information for discrimination of fixations and smooth pursuit movements is advantageous in static stimuli, without impairing the algorithm's ability to detect smooth pursuit movements in video and moving-dot stimuli. With an automated evaluation strategy, time-consuming manual annotations are avoided and a larger amount of data can be used in the evaluation process.

Rapid slowing of the atrial fibrillatory rate after administration of AZD7009 predicts conversion of atrial fibrillation.

BACKGROUND: Effects on the atrial fibrillatory rate (AFR) were studied during infusion with the combined potassium and sodium channel blocker AZD7009. METHODS AND RESULTS: Patients with persistent atrial fibrillation (AF) were randomized to AZD7009 or placebo. Thirty-five patients converted to sinus rhythm (SR) and were matched to 35 non-converters. The mean AFR before conversion was 231 fibrillations per minute (fpm), having decreased by 41%; in non-converters, it was 296 fpm at the end of infusion, having decreased by 26%. The rate of decrease was greater in converters at 5 min, -88 vs. -66 fpm (p=0.02), and at 10 min, -133 vs. -111 fpm (p=0.048). The AFR-SD and the exponential decay decreased. A small left atrial area was the only baseline predictor of conversion to SR. CONCLUSIONS: AZD7009 produced a significantly more rapid decrease of the AFR in converters than in non-converters, but the AFR at baseline was not predictive of conversion.

Detection of Non-Sustained Supraventricular Tachycardia in Atrial Fibrillation Screening.

OBJECTIVE: Non-sustained supraventricular tachycardia (nsSVT) is associated with a higher risk of developing atrial fibrillation (AF), and, therefore, detection of nsSVT can improve AF screening efficiency. However, the detection is challenged by the lower signal quality of ECGs recorded using handheld devices and the presence of ectopic beats which may mimic the rhythm characteristics of nsSVT. METHODS: The present study introduces a new nsSVT detector for use in single-lead, 30-s ECGs, based on the assumption that beats in an nsSVT episode exhibits similar morphology, implying that episodes with beats of deviating morphology, either due to ectopic beats or noise/artifacts, are excluded. A support vector machine is used to classify successive 5-beat sequences in a sliding window with respect to similar morphology. Due to the lack of adequate training data, the classifier is trained using simulated ECGs with varying signal-to-noise ratio. In a subsequent step, a set of rhythm criteria is applied to similar beat sequences to ensure that episode duration and heart rate is acceptable. RESULTS: The performance of the proposed detector is evaluated using the StrokeStop II database, resulting in sensitivity, specificity, and positive predictive value of 84.6%, 99.4%, and 18.5%, respectively. CONCLUSION: The results show that a significant reduction in expert review burden (factor of 6) can be achieved using the proposed detector.Clinical and Translational Impact: The reduction in the expert review burden shows that nsSVT detection in AF screening can be made considerably more efficiently.

Association between atrial fibrillatory rate and heart rate variability in patients with atrial fibrillation and congestive heart failure.

BACKGROUND: Even if atrial fibrillatory rate (AFR) has been related to clinical outcome in patients with atrial fibrillation (AF), its relation with ventricular response has not been deeply studied. The aim of this study was to investigate the relation between AFR and RR series variability in patients with AF. METHODS: Twenty-minute electrocardiograms in orthogonal leads were processed to extract AFR, using spatiotemporal QRST cancellation and time frequency analysis, and RR series in 127 patients (age 69 ± 11 years) with congestive heart failure (NYHA II-III) enrolled in the MUSIC study (MUerte Subita en Insufficiencia Cardiaca). Heart rate variability and irregularity were assessed by time domain parameters and entropy-based indices, respectively and their correlation with AFR investigated. RESULTS: Variability measures seem not to be related to AFR, while irregularity measures do. A significant correlation between AFR and variability parameters of heart rate variability during AF was found only in patients not treated with antiarrhythmics drugs (correlation = 0.56 P < 0.05 for pNN50), while this correlation was lost in patients taking rate- or rhythm-control drugs. A significant positive correlation between AFR and indices of RR irregularity was found, showing that a higher AFR is related to a less organized RR series (correlation = 0.33 P < 0.05 for regularity index for all patients, correlation increased in subgroups of patients treated with the same drug). CONCLUSIONS: These results suggest that a higher AFR is associated with a higher degree of irregularity of ventricular response that is observed regardless of the use of rate-controlling drugs.

Decrease of the atrial fibrillatory rate, increased organization of the atrial rhythm and termination of atrial fibrillation by AZD7009.

BACKGROUND: The atrial fibrillatory rate (AFR), on AZD7009 as compared to placebo, was investigated as a potential biomarker for electrophysiological effect in early antiarrhythmic drug development. METHODS: Patients with permanent AF received infusions of AZD7009 and placebo in an exploratory two-way, single-blind, randomized cross-over study. The ECG was continuously recorded, and following QRST cancellation the AFR, its standard deviation (SD), the exponential decay and the atrial electrogram amplitude were determined as 3-min averages. RESULTS: The mean AFR rapidly decreased by 43% from baseline (394 ± 38 to 225 ± 61 fibrillations/min, p=0.0003) on AZD7009, but not on placebo. The SD of the AFR and the exponential decay decreased in parallel. In 2 of 8 patients, termination of AF occurred after the AFR had decreased by 58% and 53%, respectively. CONCLUSIONS: The AFR may potentially serve as a biomarker of electrophysiological effects in early evaluation of rhythm control agents.

ECG Modeling for Simulation of Arrhythmias in Time-Varying Conditions.

The present article proposes an ECG simulator that advances modeling of arrhythmias and noise by introducing time-varying signal characteristics. The simulator is built around a discrete-time Markov chain model for simulating atrial and ventricular arrhythmias of particular relevance when analyzing atrial fibrillation (AF). Each state is associated with statistical information on episode duration and heartbeat characteristics. Statistical, time-varying modeling of muscle noise, motion artifacts, and the influence of respiration is introduced to increase the complexity of simulated ECGs, making the simulator well suited for data augmentation in machine learning. Modeling of how the PQ and QT intervals depend on heart rate is also introduced. The realism of simulated ECGs is assessed by three experienced doctors, showing that simulated ECGs are difficult to distinguish from real ECGs. Simulator usefulness is illustrated in terms of AF detection performance when either simulated or real ECGs are used to train a neural network for signal quality control. The results show that both types of training lead to similar performance.

Analysis of atrial fibrillatory rate during spontaneous episodes of atrial fibrillation in humans using implantable loop recorder electrocardiogram.

Atrial fibrillatory rate (AFR) can predict outcome of interventions for atrial fibrillation (AF); however, AFR behavior at AF onset in humans is poorly described. We studied AFR during spontaneous AF episodes in patients with lone paroxysmal AF who received implantable loop recorders and had AF episodes of 1 hour or more recorded (n = 4). Mean AFR per minute was assessed from continuous implantable loop recorder electrocardiogram using spatiotemporal QRST cancellation and time-frequency analysis. Atrial fibrillatory rate increased from 290 ± 20 to 326 ± 39 fibrillations per minute during the first 3 hours (P<.05) and reached plateau then. Atrial fibrillatory rate beyond the initial 3 hours can, therefore, be considered stable and may be evaluated for prediction of intervention effect.

Left atrial appendage activity translation in the standard 12-lead ECG.

INTRODUCTION: Interatrial frequency gradient is used to guide catheter ablation of atrial fibrillation (AF). Lead V1 adequately reflects right atrial activity, but reliable tools for noninvasive estimation of right versus left fibrillatory frequency are lacking. In this study, patients with dissociated left and right atrial rhythms were studied in order to identify which surface electrocardiographic (ECG) leads that most closely reflect the left atrial activity. METHODS: Two consecutive patients with atrial tachycardia confined to the left atrial appendage (LAA) detected during catheter ablation of AF were included (2 men, 54 and 72 years old). A 12-lead ECG was recorded simultaneously with electrograms from the right and left atrial appendages (RAA/LAA). AF frequency spectra were calculated from all 12 leads using spatiotemporal QRST cancellation and Welch periodogram. The dominating atrial cycle length (DACL) in the surface ECG leads was subsequently compared with the invasively measured LAA cycle length. RESULTS: LAA activation frequency was seen as a prominent peak in the frequency-power spectrum derived from frontal plane leads as well as lead V1. The absolute difference in noninvasively and invasively measured LAA cycle length was lowest for leads aVR, II, aVF, III, and V1 in which it was in the range of 2-4 ms. CONCLUSION: Prominent left atrial component is present in the majority of standard ECG leads, including those traditionally associated with right atrial activity such as V1. Spectral analysis is able to extract the LAA component on surface ECG.

Waveform characterisation and comparison of nystagmus eye-tracking signals.

OBJECTIVE: Pathological nystagmus is a symptom of oculomotor disease where the eyes oscillate involuntarily. The underlying cause of the nystagmus and the characteristics of the oscillatory eye movements are patient specific. An important part of clinical assessment in nystagmus patients is therefore to characterise different recorded eye-tracking signals, i.e. waveforms. APPROACH: A method for characterisation of the nystagmus waveform morphology is proposed. The method extracts local morphologic characteristics based on a sinusoidal model, and clusters these into a description of the complete signal. The clusters are used to characterise and compare recordings within and between patients and tasks. New metrics are proposed that can measure waveform similarity at different scales; from short signal segments up to entire signals, both within and between patients. MAIN RESULTS: The results show that the proposed method robustly can find the most prominent nystagmus waveforms in a recording. The method accurately identifies different eye movement patterns within and between patients and across different tasks. SIGNIFICANCE: In conclusion, by allowing characterisation and comparison of nystagmus waveform patterns, the proposed method opens up for investigation and identification of the underlying condition in the individual patient, and for quantifying eye movements during tasks.

Identification of Transient Noise to Reduce False Detections in Screening for Atrial Fibrillation.

Screening for atrial fibrillation (AF) with a handheld device for recording the ECG is becoming increasingly popular. The poorer signal quality of such ECGs may lead to false detection of AF, often caused by transient noise. Consequently, the need for expert review in AF screening can become extensive. A convolutional neural network (CNN) is proposed for transient noise identification in AF detection. The network is trained using the events produced by a QRS detector, classified into either true beat detections or false detections. The CNN and a low-complexity AF detector are trained and tested using the StrokeStop I database, containing 30-s ECGs from mass screening for AF in the elderly population. Performance evaluation of the CNN-based quality control using a subset of the database resulted in sensitivity, specificity, and accuracy of 96.4, 96.9, and 96.9%, respectively. By inserting the CNN before the AF detector, the false AF detections were reduced by 22.5% without any loss in sensitivity. The results show that the number of recordings calling for expert review can be significantly reduced thanks to the identification of transient noise. The reduction of false AF detections is directly linked to the time and cost spent on expert review.

Prognostic Implications of Supraventricular Arrhythmias.

The aim of this study was to establish the prevalence and prognostic implication of progressive supraventricular arrhythmias from frequent supraventricular ectopic complexes, isolated, in bi- or trigeminy, to supraventricular tachycardias with different characteristics. In the STROKESTOP I mass-screening study for atrial fibrillation (AF) in 75- and 76-year olds in Sweden, participants registered 30-second intermittent ECG twice daily for two weeks. The ECG-recordings from STROKESTOP I were re-evaluated using an automated algorithm to detect individuals with frequent supraventricular ectopic complexes or runs. Detected episodes were manually re-examined to confirm the findings. The primary endpoint was AF as ascertained from the national Swedish Patient register. Exploratory secondary endpoints were stroke and death. Median follow-up was 4.2 (interquartile range [IQR] 3.8-4.4) years. Of the examined 6,100 participants, 85% were free of significant supraventricular arrhythmia. In the 894 participants that had arrhythmia, frequent supraventricular ectopic complexes were the most common arrhythmia, n = 709 (11.6%) and irregular supraventricular tachycardias were more common than regular. Individuals with the most AF similar supraventricular tachycardias, irregular and lacking p-waves (termed micro-AF), n = 97 (1.6%) had the highest risk of developing AF (hazard ratio 4.3; 95% confidence interval [CI] 2.7-6.8). They also had increased risk of death (hazard ratio 2.0; CI 1.1-3.8). In conclusion, progression of atrial arrhythmias from supraventricular ectopic complexes to more AF-like episodes is associated with development of AF. Extended screening for AF should be considered in individuals with frequent supraventricular activity, especially in those with supraventricular tachycardias with AF characteristics.

Atrial fibrillatory rate and risk of stroke in atrial fibrillation.

AIMS: In atrial fibrillation (AF), a relation between electrocardiogram (ECG) parameters such as fibrillatory wave amplitude and stroke has been sought with conflicting results. In this study, we tested the hypothesis that the atrial fibrillatory rate of surface ECG lead V1 is related to stroke risk and may consequently be helpful for identifying high-risk patients. METHODS AND RESULTS: Atrial fibrillatory rate of 79 consecutive patients with AF and embolic stroke (age 83 +/- 7 years, 41% male) was compared with those of a matched AF population without stroke (n = 79). Atrial fibrillatory rate was determined from the surface ECG using spatiotemporal QRST cancellation and time-frequency analysis of lead V1. There was no significant difference in any clinical or echocardiographic variable in patients with stroke compared with AF controls without stroke. Atrial fibrillatory rate measured 373 +/- 55 fibrillations per minute (fpm; range 235-505 fpm) in the entire population. There was no fibrillatory rate difference between stroke patients (369 +/- 54 fpm, range 256-505 fpm) and AF controls without stroke (378 +/- 56 fpm, range 235-488 fpm). There was an inverse correlation between fibrillatory rate and age (R = -0.219, P = 0.006). Individuals aged >or=85 years had a significantly lower fibrillatory rate (356 +/- 44 fpm) than individuals aged 65-74 years (384 +/- 56 fpm, P = 0.033) and individuals aged 75-84 years (384 +/- 60 fpm, P = 0.016). In those subgroups, fibrillatory rates were, however, also similar in stroke patients and AF controls. CONCLUSION: Atrial fibrillatory rate obtained from surface ECG lead V1 is not a risk marker for stroke in AF.

Fibrillatory rate response to candesartan in persistent atrial fibrillation.

INTRODUCTION: Angiotensin-receptor blockers may exert favourable anti-arrhythmic effects in atrial fibrillation (AF), but their mechanisms are not fully understood. In this study, we tested the hypotheses that (i) candesartan reduces atrial fibrillatory rate and (ii) fibrillatory rate and its response to candesartan are related with the outcome of cardioversion. For this purpose, a post hoc subanalysis of the randomized, placebo-controlled CAPRAF (Candesartan in the Prevention of Relapsing Atrial Fibrillation) trial was performed. METHODS AND RESULTS: Patients with AF undergoing electrical cardioversion were randomized to receive candesartan 8 mg once daily (n = 58) or matching placebo (n = 66) and no additional class I or III anti-arrhythmic drugs. Fibrillatory rate was determined from ECG lead V1 at baseline and at the day of cardioversion using spatiotemporal QRST cancellation and time-frequency analysis. The median time on treatment was 29 days. Candesartan reduced fibrillatory rate [399 +/- 48 vs. 388 +/- 49 fibrillations/min (fpm), P = 0.04], but not placebo (402 +/- 58 vs. 402 +/- 61 fpm, P = 0.986). Candesartan effects were only observed if the baseline fibrillatory rate was high [>420 fpm: 445 +/- 21 vs. 415 +/- 49 fpm, P = 0.006 vs. intermediate (360-420 fpm): 397 +/- 19 vs. 391 +/- 37 fpm, P = 0.351 vs. low (<360 fpm): 326 +/- 26 vs. 338 +/- 29 fpm, P = 0.179]. Cardioversion success was 100% in patients with an on-treatment rate <360 fpm vs. 83% in patients with higher rates (P = 0.02). Risk for AF recurrence was similar in patients with low (64%), intermediate (75%), or high on-treatment rates (63%, P = 0.446) and was also independent of candesartan effects on the fibrillatory rate. CONCLUSION: In patients with persistent AF, candesartan decreases the fibrillatory rate, but this effect is restricted to patients with high baseline fibrillatory rates and is not associated with improved cardioversion outcome. Fibrillatory rates <360 fpm are associated with successful cardioversion, but not with AF recurrence.

Spatial characteristics of atrial fibrillation electrocardiograms.

BACKGROUND: The present study investigates spatial properties of atrial fibrillation (AF) by analyzing vectorcardiogram loops synthesized from 12-lead electrocardiograms (ECGs). METHODS: After atrial signal extraction, spatial properties are characterized through analysis of successive, fixed-length signal segments and expressed in loop orientation, that is, azimuth and elevation, as well as in loop morphology, that is, planarity and planar geometry. It is hypothesized that more organized AF, expressed by a lower AF frequency, is associated with decreased variability in loop morphology. Atrial fibrillation frequency is determined using spectral analysis. RESULTS: Twenty-six patients with chronic AF were analyzed using 60-second ECG recordings. Loop orientation was similar when determined from either entire 60- or 1-second segments. For 1-second segments, the correlation between AF frequency and the parameters planarity and planar geometry were 0.608 (P < .001) and 0.543 (P < .005), respectively. CONCLUSIONS: Quantification of AF organization based on AF frequency and spatial characteristics from the ECG is possible. The results suggested a relatively weak coupling between loop morphology and AF frequency when determined from the surface ECG.

Validation and clinical application of time-frequency analysis of atrial fibrillation electrocardiograms.

INTRODUCTION: Fibrillatory rates can reliably be obtained from surface ECGs during atrial fibrillation (AF) and correspond with right atrial (RA) and coronary sinus (CS) rates, while both the relation with pulmonary venous (PV) rates and determinants of fibrillatory waveform are unknown. Class III antiarrhythmic drugs prolong atrial refractoriness and decrease its dispersion, effects that may be reflected in ECG parameters. Consequently, this study sought (1) to investigate the relation between ECG fibrillatory rate and waveform characteristics with intraatrial/PV fibrillatory activity and (2) to noninvasively monitor class III antiarrhythmic drug effects in patients with AF. METHODS AND RESULTS: Thirty-six patients with drug-refractory AF who underwent catheter-based pulmonary vein isolation and had AF at the beginning of the procedure were studied. A positive correlation between V1 rates obtained by time-frequency analysis and RA (R = 0.97, P < 0.001), CS (R = .71, P < 0.001), and PV rates (R = 0.65, P = 0.001) was found. Exponential decay defined as decay of the curve that connects power maxima of dominant and harmonic frequency components correlated with RA rate dispersion (R = 0.53, P = 0.004). In amiodarone-treated patients (n = 7), V1 rate (286 +/- 64 vs. 371 +/- 40 fpm, P < 0.001) and exponential decay (1.06 +/- 0.29 vs. 1.38 +/- 0.38, P = 0.034) were lower than in patients without amiodarone (n = 29). In 19 additional patients with persistent AF, oral dofetilide treatment decreased mean fibrillatory rate from 377 +/- 57 to 294 +/- 50 fpm (P < 0.001) and exponential decay from 1.24 +/- 0.43 to 0.85 +/- 0.22 (P = 0.002). CONCLUSIONS: Fibrillatory waves of surface ECG lead V1 closely reflect right atrial, and, to a lesser degree, left atrial activity. Time-frequency analysis allows noninvasive monitoring of antiarrhythmic drug effects on fibrillatory rate and waveform.