High-resolution esophageal long-term ECG allows detailed atrial wave morphology analysis in case of atrial ectopic beats

Detection of arrhythmic atrial beats in surface ECGs can be challenging when they are masked by the R or T wave, or do not affect the RR-interval. Here, we present a solution using a high-resolution esophageal long-term ECG that offers a detailed view on the atrial electrical activity. The recorded ECG shows atrial ectopic beats with long coupling intervals, which can only be successfully classified using additional morphology criteria. Esophageal high-resolution ECGs provide this information, whereas surface long-term ECGs show poor atrial signal quality. This new method is a promising tool for the long-term rhythm monitoring with software-based automatic classification of atrial beat

Systematic, early rhythm control strategy for atrial fibrillation in patients with or without symptoms:the EAST-AFNET 4 trial

AIMS: Clinical practice guidelines restrict rhythm control therapy to patients with symptomatic atrial fibrillation (AF). The EAST-AFNET 4 trial demonstrated that early, systematic rhythm control improves clinical outcomes compared to symptom-directed rhythm control. METHODS AND RESULTS: This prespecified EAST-AFNET 4 analysis compared the effect of early rhythm control therapy in asymptomatic patients (EHRA score I) to symptomatic patients. Primary outcome was a composite of death from cardiovascular causes, stroke, or hospitalization with worsening of heart failure or acute coronary syndrome, analyzed in a time-to-event analysis. At baseline, 801/2633 (30.4%) patients were asymptomatic [mean age 71.3 years, 37.5% women, mean CHA(2)DS(2)-VASc score 3.4, 169/801 (21.1%) heart failure]. Asymptomatic patients randomized to early rhythm control (395/801) received similar rhythm control therapies compared to symptomatic patients [e.g. AF ablation at 24 months: 75/395 (19.0%) in asymptomatic; 176/910 (19.3%) symptomatic patients, P = 0.672]. Anticoagulation and treatment of concomitant cardiovascular conditions was not different between symptomatic and asymptomatic patients. The primary outcome occurred in 79/395 asymptomatic patients randomized to early rhythm control and in 97/406 patients randomized to usual care (hazard ratio 0.76, 95% confidence interval [0.6; 1.03]), almost identical to symptomatic patients. At 24 months follow-up, change in symptom status was not different between randomized groups (P = 0.19). CONCLUSION: The clinical benefit of early, systematic rhythm control was not different between asymptomatic and symptomatic patients in EAST-AFNET 4. These results call for a shared decision discussing the benefits of rhythm control therapy in all patients with recently diagnosed AF and concomitant cardiovascular conditions (EAST-AFNET 4; ISRCTN04708680; NCT01288352; EudraCT2010-021258-20)

withdrawn 2017 hrs ehra ecas aphrs solaece expert consensus statement on catheter and surgical ablation of atrial fibrillation

n/

Estimation of Arterial Pulse Wave Velocity from Doppler Radar Measurements: a Feasibility Study

Pulse wave velocity has emerged as important diagnostic parameter due to its association with various cardio-vascular disorders, such as hypertension, vascular aging, and atherosclerosis. Long-term monitoring of pulse wave velocity can be beneficial in carrying out accurate diagnosis of the underlying conditions or even for an early prediction of cardio-vascular diseases. Doppler radar has emerged as a promising technology for contact-less monitoring and assessment of physiological parameters. In this study, we aimed at: i) as a first step, assessing the feasibility of measuring arterial pulse waves at the femoral region using the Doppler radar technology, and consequently, ii) estimating the pulse transit time between the heart-femoral regions as well as between the carotid-femoral regions using simultaneous Doppler radar measurements. The results of our feasibility study demonstrate that the arterial pulse waves in the femoral region, arising due to cardiac activity, can be estimated using the Doppler radar technology in a contact-less fashion. Furthermore, simultaneous pulse wave measurements at distinct surface locations using this technique can enable contact-less estimation of the pulse transit time and consequently pulse wave velocity

High-resolution esophageal long-term ECG allows detailed atrial wave morphology analysis in case of atrial ectopic beats

Detection of arrhythmic atrial beats in surface ECGs can be challenging when they are masked by the R or T wave, or do not affect the RR-interval. Here, we present a solution using a high-resolution esophageal long-term ECG that offers a detailed view on the atrial electrical activity. The recorded ECG shows atrial ectopic beats with long coupling intervals, which can only be successfully classified using additional morphology criteria. Esophageal high-resolution ECGs provide this information, whereas surface long-term ECGs show poor atrial signal quality. This new method is a promising tool for the long-term rhythm monitoring with software-based automatic classification of atrial beats

Bufferless Compression of Asynchronously Sampled ECG Signals in Cubic Hermitian Vector Space

Asynchronous level crossing sampling analog-to-digital converters (ADCs) are known to be more energy efficient and produce fewer samples than their equidistantly sampling counterparts. However, as the required threshold voltage is lowered, the number of samples and, in turn, the data rate and the energy consumed by the overall system increases. In this paper, we present a cubic Hermitian vector-based technique for online compression of asynchronously sampled electrocardiogram signals. The proposed method is computationally efficient data compression. The algorithm has complexity O(n), thus well suited for asynchronous ADCs. Our algorithm requires no data buffering, maintaining the energy advantage of asynchronous ADCs. The proposed method of compression has a compression ratio of up to 90% with achievable percentage root-mean-square difference ratios as a low as 0.97. The algorithm preserves the superior feature-to-feature timing accuracy of asynchronously sampled signals. These advantages are achieved in a computationally efficient manner since algorithm boundary parameters for the signals are extracted a priori