Quantification of the first-order high-pass filter's influence on the automatic measurements of the electrocardiogram.

BACKGROUND AND OBJECTIVE: The first-order high-pass filter (AC coupling) has previously been shown to affect the ECG for higher cut-off frequencies. We seek to find a systematic deviation in computer measurements of the electrocardiogram when the AC coupling with a 0.05 Hz first-order high-pass filter is used. METHODS: The standard 12-lead electrocardiogram from 1248 patients and the automated measurements of their DC and AC coupled version were used. We expect a large unipolar QRS-complex to produce a deviation in the opposite direction in the ST-segment. RESULTS: We found a strong correlation between the QRS integral and the offset throughout the ST-segment. The coefficient for J amplitude deviation was found to be -0.277 µV/(µV⋅s). CONCLUSIONS: Potential dangerous alterations to the diagnostically important ST-segment were found. Medical professionals and software developers for electrocardiogram interpretation programs should be aware of such high-pass filter effects since they could be misinterpreted as pathophysiology or some pathophysiology could be masked by these effects.

A Correction Formula for the ST-Segment Measurements of AC-Coupled Electrocardiograms.

GOAL: The ST segment of an electrocardiogram (ECG) is very important for the correct diagnosis of an acute myocardial infarction. Most clinical ECGs are recorded using an ACcoupled ECG amplifier. It is well known, that first-order high-pass filters used for the AC coupling can affect the ST segment of an ECG. This effect is stronger the higher the filter's cut-off frequency is and the larger the QRS integral is. We present a formula that estimates these changes in the ST segment and therefore allows for correcting ST measurements that are based on an ACcoupled ECG. METHODS: The presented correction formula can be applied when only four parameters are known: the possibly estimated QRS area A, the QRS duration W, the beat-to-beat interval TRR, and the filter time constant T, further, the time point Tj to correct-after the J point-must be specified. RESULTS: The formula is correct within 0.6% until 40% ms after the J point and within 6% until 80 ms after the J point. CONCLUSION AND SIGNIFICANCE: It is not necessary to have the raw data available and the formula therefore opens up the possibility of reevaluating studies that are based on ACcoupled ECGs and compare the results of such studies with studies that are based on newer, DC-coupled ECGs.

Digital DC-Reconstruction of AC-Coupled Electrophysiological Signals with a Single Inverting Filter.

Since the introduction of digital electrocardiographs, high-pass filters have been necessary for successful analog-to-digital conversion with a reasonable amplitude resolution. On the other hand, such high-pass filters may distort the diagnostically significant ST-segment of the ECG, which can result in a misleading diagnosis. We present an inverting filter that successfully undoes the effects of a 0.05 Hz single pole high-pass filter. The inverting filter has been tested on more than 1600 clinical ECGs with one-minute durations and produces a negligible mean RMS-error of 3.1*10(-8) LSB. Alternative, less strong inverting filters have also been tested, as have different applications of the filters with respect to rounding of the signals after filtering. A design scheme for the alternative inverting filters has been suggested, based on the maximum strength of the filter. With the use of the suggested filters, it is possible to recover the original DC-coupled ECGs from AC-coupled ECGs, at least when a 0.05 Hz first order digital single pole high-pass filter is used for the AC-coupling.

Development of a toolbox for electrocardiogram-based interpretation of atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) develops as a consequence of an underlying heart disease such as fibrosis, inflammation, hyperthyroidism, elevated intra-atrial pressures, and/or atrial dilatation. The arrhythmia is initiated by, or depends on, ectopic focal activity. Autonomic dysfunction may also play a role. However, in most patients, the actual cause of AF is difficult to establish, which hampers the selection of the optimal mode of treatment. This study aims to develop tools for assisting the physician's decision-making process. METHODS: Signal analytical methods have been developed for optimizing the assessment of the complexity of AF in all of the standard 12-lead signals. The development involved an evaluation of methods for reducing the signal components stemming from the electric activity of the ventricles (QRST suppression). The methods were tested on simulated recordings, on clinical recordings on patients in AF, and on patients exhibiting atrial flutter (AFL) and atrial tachycardia. The results have been published previously. Subsequently, the implementation of the algorithms in a commercially available electrocardiogram (ECG) recorder, an implementation referred to as its AF-Toolbox, has been carried out. The performance of this implementation was tested against those observed during the development stage. In addition, an improved visualization of the specific ECG components was implemented. This was enabled by providing a separate view on ventricular and atrial activity, which resulted from the steps implied in the QRST suppression. Furthermore, a search was initiated for identifying meaningful features in the cleaned up atrial signals. RESULTS: When testing the implementation of the previously developed methods in the Toolbox on simulated and clinical data, the suppression of ventricular activity in the ECG produced residuals down to the level of physiologic background noise, in agreement with those reported on previously. The QRST suppression resulted in a better visualization of the atrial signals in AF, atrial AFL, sinus rhythm in the presence of atrioventricular blocks, or ectopic beats. Classifiers for AF and AFL that have been defined so far include the distinct spectral components (multiple basic frequencies), exhibiting distinct dominance in specific leads. The annotations of ventricular and atrial activities, ventricular and atrial trigger, as well as ratio between atrial and ventricular rates were greatly facilitated. The time diagram of ventricular and atrial triggers provides an additional view on rhythm disturbances. CONCLUSIONS: The AF-Toolbox that is currently developed for clinical applications has the potential of reliably detecting and classifying AF, as well as to correctly describe atrioventricular conduction, propagation blocks and/or ectopic beats. Based on the results obtained, a first industrial prototype has been built, which will be used to assess its performance in a routine clinical environment. The availability of this tool will facilitate the search for meaningful signal features for identifying the source of AF in individual patients.

Meet the challenge of high-pass filter and ST-segment requirements with a DC-coupled digital electrocardiogram amplifier.

BACKGROUND: The high-pass filter (HPF) in an electrocardiogram (ECG) amplifier can distort the ST segment required for ischemia interpretation. Therefore, the current standards and guidelines require -3 dB for monitoring and -0.9 dB for diagnostic purposes at 0.67 Hz. In addition, a minimal reaction to a rectangular pulse of 300 microV has to be proven. We raise the question of why the design of a DC-coupled digital ECG amplifier is reasonable when today the AC-coupled digital ECG amplifier including a 0.05-Hz HPF works so well, meets all required standards, and is already safe. We make the hypothesis that a digital DC-coupled ECG amplifier can as well meet the requirements and guarantee the same safety levels at the same time provide a higher degree of freedom for future improvements of the ECG signal quality. METHODS: Firstly, a historical research of the origin of the 0.05-Hz requirement has been made. Secondly, triangular pulses simulating unipolar QRS complexes have been passed through a digital filter to get qualitative results of the HPF response. And finally, to quantitatively describe the filter response, corresponding test requirement signals have been passed through a digital filter to simulate the HPF behavior, therefore understanding the reasons for the required tests. RESULTS: The oldest reference found to the 0.05-Hz filter dates from 1937. At that time, DC-coupled analogue ECG amplifiers were used. The simulation of the AC-coupled ECG amplifier with a first-order analogue HPF shows that the rectangular 300-microV pulse is a phase requirement and more restrictive than the frequency requirements. The phase requirement in fact corresponds to the requirement of a 0.05-Hz first-order analogue HPF (-3 dB) even if -0.9 dB at 0.67 Hz is required. The DC-coupled ECG amplifier (without an analogue HPF and during online and off-line acquisition) fulfils the phase and frequency requirements, just as the digital AC-coupled ECG amplifier does. CONCLUSIONS: An AC-coupled ECG amplifier based on a first-order analogue HPF must have a maximum cutoff frequency of 0.05 Hz or requires a phase equalizer causing a delay of the acquired ECG. Because the desired delay during online acquisition should be short, the solution is practical but could be improved. Not the frequency cutoff of the HPF but the phase distortion of such a filter should be discussed. The DC-coupled ECG amplifier is as safe as the AC-coupled ECG amplifier; but it provides a higher degree of freedom for future filter designs certainly improving the ECG signal quality, while the safety can be guaranteed. Furthermore, the DC-coupled ECG amplifier allows investigation of the HPF, which is not easily possible when an AC-coupled ECG amplifier including the HPF is to be investigated.

Improving automatic analysis of the electrocardiogram acquired during magnetic resonance imaging using magnetic field gradient artefact suppression.

The electrocardiogram (ECG) used for patient monitoring during magnetic resonance imaging (MRI) unfortunately suffers from severe artefacts. These artefacts are due to the special environment of the MRI. Modeling helped in finding solutions for the suppression of these artefacts superimposed on the ECG signal. After we validated the linear and time invariant model for the magnetic field gradient artefact generation, we applied offline and online filters for their suppression. Wiener filtering (offline) helped in generating reference annotations of the ECG beats. In online filtering, the least-mean-square filter suppressed the magnetic field gradient artefacts before the acquired ECG signal was input to the arrhythmia algorithm. Comparing the results of two runs (one run using online filtering and one run without) to our reference annotations, we found an eminent improvement in the arrhythmia module's performance, enabling reliable patient monitoring and MRI synchronization based on the ECG signal.

Electrocardiogram on a chip: overview and first experiences of an electrocardiogram manufacturer of medium size.

The integration of an electrocardiogram (ECG) device into a chip is already well known in the field of implanted devices, such as pacemakers. For noninvasive electrocardiology, this approach has not been used on a broad scale commercially. The extension of electrocardiology to telemetry, home care, and special applications as in magnetic resonance imaging has spawned a new interest in highly miniaturized ECG devices. In our company, we are aiming for using highly integrated devices exactly in these fields. On one hand, the home monitoring market ("eHealth," "pHealth") requires small and lightweight devices ("ECG in an electrode"); on the other hand, the use of an ECG device within a hostile environment as in an magnetic resonance imaging machine with strong electromagnetic fields requires small dimensions of the device. Of these 2 fields, the one of home monitoring is the most promising. There is a large population in need of such monitoring (eg, patients with congestive heart failure), and the cost issue in medical care drives the market in this direction. Projects in both fields will be presented as well as the first experiences as a middle-sized manufacturer in trying to produce an integrated ECG "device."