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Several white papers have been published on general requirements for 5G in the health vertical. As 5G research and implementation continue more detailed real world information for application research are needed. This paper is focusing on the requirements for telemetric cardiac monitoring based on real world experiences from a joint project on early geriatric rehabilitation of elderly patients in a care of the elderly department after minimal invasive and conservative treatment in a highly specialized cardiology unit in Leipzig, Germany.

In this study, several morphological parameters to assess the P-wave from the surface electrocardiogram are proposed and analysed. In order to evaluate spatial features, two parameters are defined: P-wave complexity and P-wave residuum. Additionally, in order to evaluate beat to beat features, the P-wave regularity is defined. All three parameters are computed from the eigenvalue decomposition of the original data, and were applied on patients who suffered from either dilated or ischemic cardiomyopathy. The results showed that both the P-wave complexity and P-wave regularity are able to find and emphasize interpatient differences, whereas the results of P-wave residuum where rather similar for all patients.

The strategy of rate control during atrial fibrillation (AF) essentially deals with efforts to utilize and adjust the filtering properties of the atrioventricular (AV) node, allowing AF to continue and ensure that ventricular rate is controlled. In this work, a new tool based on the 3D Poincare plots is developed for the characterization of the ventricular response (VR) and the clinical evaluation of rate control therapies. Mechanisms underlying atrioventricular conduction during AF remain unclear. The role of the dual pathway AV nodal electrophysiology and the effects of the AV node modifications are still being an incognita. RR interval clusters exhibiting harmonic behaviour have been quantified suggestive of an underlying AV conduction ratio.

The present study deals with detection of intra-atrial wavefronts from atrial activation times in adjacent bipolar electrograms. A statistic of the delays within each wave-front was calculated and served as a basis for quantifying the wavefront consistency as well as the propagation of the electrical activity along the catheter. The database consisted of 19 patients for which five electrograms were recorded simultaneously during 10 s. The analysis resulted in 38plusmn2 complete wavefronts per patient, i.e., wavefronts consisting of one activation from each recording site. Two parameters were evaluated for quantifying wavefront consistency, which together with the propagation profile well reflect the overall wavefront timing. In most cases, electrical activity was observed first in the high septal right atrium, and then spread along the catheter.

Electrical atrial activation during atrial fibrillation shows an uncoordinated pattern. Invasive studies and computer models have shown that functional and anatomical barriers can sustain atrial fibrillation. Mechanisms involved in the fibrillatory process are multiple wave reentry, rotors and spiral waves. We have developed a new diagnostic tool with the aim to characterize electrical activation patterns during atrial fibrillation from the body surface. Non-invasive high density mapping using 56 surface electrodes placed on the chest and back of six patients with persistent atrial fibrillation was performed. For the first time, we observed different activation patterns of atrial fibrillation from the body surface: single or multiple wavefronts with different degrees of repeatability. Further study of the activation patterns could be useful in the diagnosis and individual selection of the best treatment with atrial fibrillation.

Atrial fibrillation (AF) is an arrhythmia characterized by highly irregular atrial depolarization. Among various commonly used antiarrhythmic drugs, flecainide is known to decrease conduction velocity in a rate-dependent manner. The aim of this study was to establish a protocol to monitor flecainidepsilas rate-dependent conduction slowing, during physiologic increases in heart rate (HR) in patients with AF. QRS duration at rest and during symptom-limited bicycle exercise stress was measured in 9 patients with persistent AF before and during oral flecainide administration. Flecainide-induced QRS duration prolongation was more pronounced during exercise than at rest. In patients with AF, this characteristic can be monitored and quantified by measuring QRS duration under resting and exercise conditions, helping in determination of antiarrhythmic efficacy and preventing proarrhythmic effects in the individual patient.

In atrial fibrillation (AF), the body surface signal pattern varies considerably from one patient to another as well as over time. We have developed a new method for ECG-based characterization of AF which explores the morphology of the f-waves. Following QRST cancellation, the method divides the atrial signal into short blocks and performs a model-based analysis of each block. The blocks are then clustered into different waveform patterns. The method was applied to a database of 36 patients (10-s recordings) with organized AF. The results show that the different waveforms in AF are well represented by the proposed model. Each recording was, in average, represented by 3 clusters of which the main cluster covered 31% of the blocks. In lead V1, the typical phase relationship between the fundamental and first harmonic was -82 degrees, indicating sawtooth-like waves with a steeper downslope than upslope.

The present study investigates spatial properties of atrial fibrillation (AF) by analyzing VCG loops synthesized from 12-lead ECGs. The atrial signal is extracted using spatiotemporal QRST cancellation, and spatial properties are characterized through joint analysis of successive fixed-length signal segments. The significance of spatial (loop morphology) parameters is studied in relation to AF frequency, hypothesizing that more organized AF, being expressed by lower frequency, is associated with decreased variability in loop morphology. The results showed that loop orientation can be determined from global analysis (i.e., the entire 60-s segment is used) or the mean of segment-based analysis, both types of analysis leading to similar results. The hypothesis that more organized AF is associated with decreased variability in loop morphology was to some extent confirmed for the parameters planarity and planar geometry; for 1-s segments, the correlation to AF frequency was 0.608 (ples0.001) and 0.543 (ples0.005).

During atrial fibrillation (AF), time-frequency analysis of atrial signal has been applied to describe fibrillatory frequency trends. Recently, temporal changes in spectral shape have been investigated using the spectral profile technique. This profile is computed recursively by fitting each short-time log-spectrum to a spectral template, using amplitude scaling and frequency shifting. The purpose of the present study was to develop a Gaussian mixture model of the spectral profile in order to characterize the shape of AF waveforms. A novel index is introduced, the so-called harmonic index (HI), which reflects properties of the fundamental frequency peak and related harmonics peaks as estimated from the model. The index was tested on recordings from 9 patients with persistent AF, obtained before and after exercise testing. The HI succeeded in monitoring the response to exercise, i.e. change in the spectral profile to a less harmonic pattern, which is consistent with a reduction in AF organization (HI: 0.61+0.11 vs. 0.50plusmn0.19, rest vs. exercise; p

Our approach to predicting spontaneous termination of atrial fribulation (AF) is based on parameters derived from the time-frequency distribution of the residual ECG signal, resulting from spatiotemporal cancellation of QRST complexes. Each consecutive, logarithmically scaled spectrum of the time-frequency distribution of the residual ECG is modeled as a frequency shifed and amplitude scaled version of a spectral profile. Parameters characterizing AE such as fundamental frequency, amplitude, and wavefonn of the fibrillation waves, are then extracted from the spectral profile. The waveform of the spectral profile is used to distinguish AF from sinus rhythm and noise, so that occasional episodes of sinus rhyrhm and noise can be excluded. Using these parameters, 95% of the ECGs from the training set, and 90% from the test set was correctly classified as nonterminating and terminating AF respectively.

This study explored the potential clinical value of Time-Frequency Analysis (TFA) of the sulface ECG for monitoring and predicting atrial drug action in atrial fibrillation (AF). Baseline fwo-minute ECG recordings were made in 42 patients with persisient AF and after oral Jecainide (n=24) or amiodarone (n=18) initiation. Afrer spariotemporal QRXT cancellation, TFA was perjbrmed and ( I ) mean fibrillatory rate, (2) rate stability, and (3) exponential decay of fundamental and harmonic frequency components were determined. Patienrs in whom AF terminated (n=I2) had a lower atrial rate and a smaller exponential decay at baseline than patients who remained in AF. In the remaining 30 patients, drug loading organized AF as expressed by ( 1 ) decrease of atrial rate, (2) increase of ECG segments with stable AF, and (3) decrease of exponentid decay. In conclusion, TFA has the potential to predict and monitor individual antiarrhythmic drug responses in AF.

Dominant atrial rates obtained from the sugace electrocardiogram (ECG) during atrial fibrillation (AF) have been shown to reflect right atrial (RA) and coronary sinus (CS} rates. The relation of pulmonary venous (PV) fibrillatory rate to rates obtained from she standard 12- lead surfuce ECG, is, however, not known. Baseline IO-second 12-lead ECG recordings were made in 25 consecutive patients undergoing PV isolation for AF. After spatiotemporal QRST cancellation, Fourierbased time-frequency analysis was pelformed and atrial fibrillatory rate was determined. Mean PV fibrillatory rates were slightly higher than RA and CS rates, with no difference between right and left PVs. RA {R=.865, p

A new method for characterization of simultaneous intra-atrial and ECG recordings during atrial fibrillation (AF) is presented. With different preprocessing, both types of signals are characterized using a logarithmic time-frequency distribution from which trends of frequency, regularity, morphology (only ECG) and signal quality are extracted. The objective of the study is to relate ECG measures of rate and morphology to measures of intra-atrial organisation. The algorithm has been tested on a database with simultaneous ECG and right atrial recordings from 34 patients with drug-refractory AF. The average frequency in lead V1 was 5.91 Hz (std=0.94) and the average exponential decay of harmonic magnitudes (reflecting the morphology) in V1 was 1.31 (std=0.38); their correlation coefficient was 0.53 (p

Analysis of high frequency components of the QRS complex in the standard twelve-lead ECG has been suggested as indicator for ischemia, as significant changes in morphology and voltage amplitude have been observed. Changes in high frequency components for old myocardial infarction are less specific and their advantages over the unfiltered ECG are unclear. However, lead positions outside the standard ECG have not been explored systematically. In this study, we extend the number of leads included in high frequency QRS analysis looking for differences between controls and old anterior myocardial infarctions by applying body surface mapping. Differences in the number of leads presenting reduction in the high frequency content of the QRS complex, as well as the temporal width of this reduction, have been found between patients and normals, suggesting markers for electrocardiographic assessment of conduction slowing

Determination of spectral parameters from surface electrocardiograms (ECG) during atrial fibrillation (AF) may prove useful for understanding underlying pathomechanisms and selecting optimal treatment. Dominant fibrillatory frequency is the most commonly used parameter today, but bandwidth (BW) and an index of temporal frequency stability (IS) have also been described. However, no study has systematically evaluated the influence of parameter settings on inter individual differences and distinguishing antiarrhythmic drug effects. This study included 20 patients with persistent AF. ECG recordings were taken before and after amiodarone administration. The atrial fibrillatory component was extracted from ECG by principal component analysis techniques, and the spectral properties were obtained from the Welch's periodogram and the time-frequency transform. The following parameters were evaluated: BW, instantaneous main frequency and IS. Several parameter settings were studied in order to determine the values that maximize interindividual differences and allow monitoring of drug effects. Baseline frequency measured 6.54plusmn0.53 Hz (range 5.7 to 7.4 Hz) and was reduced to 5.64plusmn0.54 Hz (range 4.8 to 6.5 Hz) by amiodarone (p

Automatic analysis of the frequency content of the fibrillatory baseline on the standard surface ECG during atrial fibrillation (AF) accurately reflects the average frequency of atrial fibrillatory activity. Atrial fibrillatory frequency (f) was determined from surface ECG recordings. After filtering averaged QRST complexes were subtracted in one-minute ECG segments. The resulting signal was subjected to Fourier transformation and the dominant f was determined in the 3 to 12 Hz frequency range. Assessment of f in 30 patients with persistent AF (18 male, 12 female, mean age 60/spl plusmn/11 years) showed a decrease at night (6.8/spl plusmn/0.7 Hz at 10 AM; 6.7/spl plusmn/0.7 Hz at 4 PM; 6.6/spl plusmn/0.7 Hz at 10 PM and 6.4/spl plusmn/0.7 Hz at 4 AM, p=.028). In 12 patients (12 male, mean age 55/spl plusmn/9 years) oral amiodarone (n=5), sotalol (n=5) or flecainide (n=2) reduced mean f from 7.0/spl plusmn/0.5 Hz to 6.3/spl plusmn/0.6 Hz (p=.003) without AF termination. Atrial fibrillatory frequency determined from ECG recordings shows a circadian pattern with a lower frequency at night. This test may be used to monitor directly the atrial response to antiarrhythmic medication.