Thomas Niederhauser

Software-based detection of atrial fibrillation in long-term ECGs.

BACKGROUND Atrial fibrillation (AF) is common and may have severe consequences. Continuous long-term electrocardiogram (ECG) is widely used for AF screening. Recently, commercial ECG analysis software was launched, which automatically detects AF in long-term ECGs. It has been claimed that such tools offer reliable AF screening and save time for ECG analysis. However, this has not been investigated in a real-life patient cohort. OBJECTIVE To investigate the performance of automatic software-based screening for AF in long-term ECGs. METHODS Two independent physicians manually screened 22,601 hours of continuous long-term ECGs from 150 patients for AF. Presence, number, and duration of AF episodes were registered. Subsequently, the recordings were screened for AF by an established ECG analysis software (Pathfinder SL), and its performance was validated against the thorough manual analysis (gold standard). RESULTS Sensitivity and specificity for AF detection was 98.5% (95% confidence interval 91.72%-99.96%) and 80.21% (95% confidence interval 70.83%-87.64%), respectively. Software-based AF detection was inferior to manual analysis by physicians (P < .0001). Median AF duration was underestimated (19.4 hours vs 22.1 hours; P < .001) and median number of AF episodes was overestimated (32 episodes vs 2 episodes; P < .001) by the software. In comparison to extensive quantitative manual ECG analysis, software-based analysis saved time (2 minutes vs 19 minutes; P < .001). CONCLUSION Owing to its high sensitivity and ability to save time, software-based ECG analysis may be used as a screening tool for AF. An additional manual confirmatory analysis may be required to reduce the number of false-positive findings.

The optimal lead insertion depth for esophageal ECG recordings with respect to atrial signal quality

BACKGROUND Diagnosing supraventricular arrhythmias by conventional long-term ECG can be cumbersome because of poor p-waves. Esophageal long-term electrocardiography (eECG) has an excellent sensitivity for atrial signals and may overcome this limitation. However, the optimal lead insertion depth (OLID) is not known. METHODS We registered eECGs at different lead insertion depths in 27 patients and analyzed 199,716 atrial complexes with respect to signal amplitude and slope. Correlation and regression analyses were used to find a criterion for OLID. RESULTS Atrial signal amplitudes and slopes significantly depend on lead insertion depth. OLID correlates with body height (rSpearman=0.71) and can be estimated by OLID [cm]=0.25*body height[cm]-7cm. At this insertion depth, we recorded the largest esophageal atrial signal amplitudes (1.27±0.86mV), which were much larger compared to conventional surface lead II (0.19±0.10mV, p<0.0001). CONCLUSION The OLID depends on body height and can be calculated by a simple regression formula.

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.

Esophageal Long-Term ECG Reveals Paroxysmal Atrial Fibrillation

A 79-year-old man was referred for coronary angiography because of atypical chest pain. The patients medical history included a myocardial infarction 5 years previously and well-controlled arterial hypertension. Three months before this admission he reported atypical chest pain, sometimes associated with palpitations lasting seconds up to a few minutes. Hence, he underwent ambulant 24-hour ECG, which revealed frequent atrial premature beats but no other arrhythmia. On admission, the patient was in sinus rhythm. Echocardiography showed normal ventricular function without structural heart disease. After successful percutaneous transluminal coronary angioplasty, the patient was included in a study …

Electrodes for Long-Term Esophageal Electrocardiography

The emerging application of long-term and high-quality ECG recording requires alternative electrodes to improve the signal quality and recording capability of surface skin electrodes. The esophageal ECG has the potential to overcome these limitations but necessitates novel recorder and lead designs. The electrode material is of particular interest, since the material has to ensure conflicting requirements like excellent biopotential recording properties and inertness. To this end, novel electrode materials like PEDOT and silver-PDMS as well as established electrode materials such as stainless steel, platinum, gold, iridium oxide, titanium nitride, and glassy carbon were investigated by long-term electrochemical impedance spectroscopy and model-based signal analysis using the derived in vitro interfacial properties in conjunction with a dedicated ECG amplifier. The results of this novel approach show that titanium nitride and iridium oxide featuring microstructured surfaces did not degrade when exposed to artificial acidic saliva. These materials provide low electrode potential drifts and insignificant signal distortion superior to surface skin electrodes making them compatible with accepted standards for ambulatory ECG. They are superior to the noble and polarizable metals such as platinum, silver, and gold that induced more signal distortions and are superior to esophageal stainless steel electrodes that corrode in artificial saliva. The study provides rigorous criteria for the selection of electrode materials for prolonged ECG recording by combining long-term in vitro electrode material properties with ECG signal quality assessment.

Graphics Processor Unit Based Parallelization of Optimized Baseline Wander Filtering Algorithms for Long-term Electrocardiography

Long-term electrocardiogram (ECG) often suffers from relevant noise. Baseline wander in particular is pronounced in ECG recordings using dry or esophageal electrodes, which are dedicated for prolonged registration. While analog high-pass filters introduce phase distortions, reliable offline filtering of the baseline wander implies a computational burden that has to be put in relation to the increase in signal-to-baseline ratio (SBR). Here, we present a graphics processor unit (GPU)-based parallelization method to speed up offline baseline wander filter algorithms, namely the wavelet, finite, and infinite impulse response, moving mean, and moving median filter. Individual filter parameters were optimized with respect to the SBR increase based on ECGs from the Physionet database superimposed to autoregressive modeled, real baseline wander. A Monte-Carlo simulation showed that for low input SBR the moving median filter outperforms any other method but negatively affects ECG wave detection. In contrast, the infinite impulse response filter is preferred in case of high input SBR. However, the parallelized wavelet filter is processed 500 and four times faster than these two algorithms on the GPU, respectively, and offers superior baseline wander suppression in low SBR situations. Using a signal segment of 64 mega samples that is filtered as entire unit, wavelet filtering of a seven-day high-resolution ECG is computed within less than 3 s. Taking the high filtering speed into account, the GPU wavelet filter is the most efficient method to remove baseline wander present in long-term ECGs, with which computational burden can be strongly reduced.

A Baseline Wander Tracking System for Artifact Rejection in Long-Term Electrocardiography

Long-term electrocardiogram (ECG) signals might suffer from relevant baseline disturbances during physical activity. Motion artifacts in particular are more pronounced with dry surface or esophageal electrodes which are dedicated to prolonged ECG recording. In this paper we present a method called baseline wander tracking (BWT) that tracks and rejects strong baseline disturbances and avoids concurrent saturation of the analog front-end. The proposed algorithm shifts the baseline level of the ECG signal to the middle of the dynamic input range. Due to the fast offset shifts, that produce much steeper signal portions than the normal ECG waves, the true ECG signal can be reconstructed offline and filtered using computationally intensive algorithms. Based on Monte Carlo simulations we observed reconstruction errors mainly caused by the non-linearity inaccuracies of the DAC. However, the signal to error ratio of the BWT is higher compared to an analog front-end featuring a dynamic input ranges above 15 mV if a synthetic ECG signal was used. The BWT is additionally able to suppress (electrode) offset potentials without introducing long transients. Due to its structural simplicity, memory efficiency and the DC coupling capability, the BWT is dedicated to high integration required in long-term and low-power ECG recording systems.

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.

Electrocardiographic ST-segment monitoring during controlled occlusion of coronary arteries ☆ ☆☆

BACKGROUND Ischemia monitoring cannot always be performed by 12-lead ECG. Hence, the individual performance of the ECG leads is crucial. No experimental data on the ECGs specificity for transient ischemia exist. METHODS In 45 patients a 19-lead ECG was registered during a 1-minute balloon occlusion of a coronary artery (left anterior descending artery [LAD], right coronary artery [RCA] or left circumflex artery [LCX]). ST-segment shifts and sensitivity/specificity of the leads were measured. RESULTS During LAD occlusion, V3 showed maximal ST-segment elevation (0.26mV [IQR 0.16-0.33mV], p=0.001) and sensitivity/specificity (88% and 80%). During RCA occlusion, III showed maximal ST-elevation (0.2mV [IQR 0.09-0.26mV], p=0.004), aVF had the best sensitivity/specificity (85% and 68%). During LCX occlusion, V6 showed maximal ST-segment elevation (0.04mV [IQR 0.02-0.14mV], p=0.005), and sensitivity/specificity was (31%/92%) but could be improved (63%/72%) using an optimized cut-off for ischemia. CONCLUSION V3, aVF and V6 show the best performance to detect transient ischemia.

Atrial waveform analysis using esophageal long-term electrocardiography reveals atrial ectopic activity

A 59-year-old male patient without the history of heart disease was referred for coronary angiography due to typical chest pain and signs of myocardial ischemia during exercise stress test. On admission, the patient was in sinus rhythm. After successful PCI, the patient was enrolled in a study to investigate esophageal long-term electrocardiography (eECG) comprising simultaneous rhythm monitoring with surface and esophageal leads during 16 h. The surface ECG (sECG) was recorded using a two-channel Holter ECG recorder with a sampling frequency of 1,024 Hz allowing continuous rhythm monitoring for 7 days (Lifecard CF, Spacelabs Healthcare, USA). The eECG was recorded using an esophageal ECG electrode (Esosoft 6S, FIAB, Italy) connected to a dedicated two-channel eECG recorder—a proprietary development—with a sampling frequency of 512 Hz. We registered two bipolar channels (interelectrode spacings of 60 and 15 mm). The eECG was well tolerated; the patient reported only a slight pharyngeal foreign body feeling without any impact on his common daily activities such as eating, talking and sleeping. The sECG was analyzed using an automatic beat classifier system (Pathfinder, Spacelabs Healthcare, USA). The software correctly detected five atrial premature beats (APB’s) but no other atrial arrhythmias. In the eECG, we unmasked another 40 APB’s, as well as 178 episodes with atrial ectopic rhythm [mean duration ± SD 25 ± 31 beats (Fig. 1)]. This report illustrates the limited sensitivity of surface long-term ECG for atrial rhythm disorders. For the sECG, software-based automatic classification of atrial arrhythmias is accomplished by calculating the ratio of the R–Rinterval to be classified and the preceding R–R-interval(s). This quotient is then compared to a coupling interval threshold, e.g., the Pathfinder software uses by default 66 % of the preceding R–R-interval duration. The number of detected atrial arrhythmias strongly depends on this threshold: atrial ectopic beats are only identifiable if they are premature enough as compared to this threshold. The sECG uses R–R-intervals as surrogate markers of the true atrial activity, while morphologic features of atrial signals are not considered. The lack of a direct classifier for atrial arrhythmias is a major limitation of sECG monitoring in cases without evident change in R–R cycle duration. Moreover, reliable detection of atrial arrhythmias is of increasing importance for risk stratification, because it has been shown that excessive supraventricular ectopic activity [1] as well as atrial premature beats [2–4] are associated with an increased risk of stroke and atrial fibrillation. Esophageal electrocardiography may provide an elegant way out by offering excellent atrial signals that additionally allow waveform analysis for the direct and reliable classification of atrial rhythm. Lead movements due to eating or respiration can confound esophageal electrocardiography. We exclude that the morphologic changes are caused by such artifacts for the ClinicalTrials.gov Identifier: NCT01436344.