Publications

2023

  • [DOI] F. El-Hamad, H. Ernst, M. Schmidt, S. S. Shahrbabaki, and M. Baumert, “Contributors to Beat-to-Beat Stroke Volume Variability during Acute Mental Stress in Healthy Volunteers,” in 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023, p. 1–4.
    [Bibtex] 
    @inproceedings{el-hamad_contributors_2023,
title = {Contributors to Beat-to-Beat Stroke Volume Variability during Acute Mental Stress in Healthy Volunteers},
booktitle = {2023 45th {{Annual International Conference}} of the {{IEEE Engineering}} in {{Medicine}} \& {{Biology Society}} ({{EMBC}})},
author = {El-Hamad, Fatima and Ernst, Hannes and Schmidt, Martin and Shahrbabaki, Sobhan Salari and Baumert, Mathias},
year = {2023},
month = jul,
pages = {1--4},
issn = {2694-0604},
doi = {10.1109/EMBC40787.2023.10340083},
urldate = {2024-04-18},
abstract = {Acute mental stress elicits sympathetic activation, increasing heart rate and shortening the QT interval, but it is unknown whether this activation translates to stroke volume (SV) changes. Multivariate power spectral decomposition was used to assess the influence of heart rate and QT variabilities on SV variability at rest and during acute mental stress. Acute mental stress elicits mild but statistically significant increase in SV variability. Heart rate variability contributes almost one third of SV variability, while the contribution of QT variability is below 3\%. In conclusion, although heart rate variability appears to contribute directly to increase in SV variability during acute mental stress, most of SV variability is attributed to sources independent of heart rate and QT variabilities.Clinical Relevance---Acute mental stress elicits small fluctuations in stroke volume in healthy volunteers. Its significance for clinical populations remains to be established.},
keywords = {Biology,Fluctuations,Heart rate variability,Human factors,Sociology,Statistics},
file = {C\:\\Users\\martin\\Zotero\\storage\\HY9A69IS\\El-Hamad et al. - 2023 - Contributors to beat-to-beat stroke volume variabi.pdf;C\:\\Users\\martin\\Zotero\\storage\\2AYPITN9\\10340083.html}
}
  • [DOI] H. Ernst, M. Scherpf, S. Pannasch, J. R. Helmert, H. Malberg, and M. Schmidt, “Assessment of the Human Response to Acute Mental Stress–An Overview and a Multimodal Study,” PLOS ONE, vol. 18, iss. 11, p. e0294069, 2023.
    [Bibtex] 
    @article{ernst_assessment_2023,
title = {Assessment of the Human Response to Acute Mental Stress--{{An}} Overview and a Multimodal Study},
author = {Ernst, Hannes and Scherpf, Matthieu and Pannasch, Sebastian and Helmert, Jens R. and Malberg, Hagen and Schmidt, Martin},
year = {2023},
month = nov,
journal = {PLOS ONE},
volume = {18},
number = {11},
pages = {e0294069},
publisher = {Public Library of Science},
issn = {1932-6203},
doi = {10.1371/journal.pone.0294069},
urldate = {2024-04-18},
abstract = {Numerous vital signs are reported in association with stress response assessment, but their application varies widely. This work provides an overview over methods for stress induction and strain assessment, and presents a multimodal experimental study to identify the most important vital signs for effective assessment of the response to acute mental stress. We induced acute mental stress in 65 healthy participants with the Mannheim Multicomponent Stress Test and acquired self-assessment measures (Likert scale, Self-Assessment Manikin), salivary {$\alpha$}-amylase and cortisol concentrations as well as 60 vital signs from biosignals, such as heart rate variability parameters, QT variability parameters, skin conductance level, and breath rate. By means of statistical testing and a self-optimizing logistic regression, we identified the most important biosignal vital signs. Fifteen biosignal vital signs related to ventricular repolarization variability, blood pressure, skin conductance, and respiration showed significant results. The logistic regression converged with QT variability index, left ventricular work index, earlobe pulse arrival time, skin conductance level, rise time and number of skin conductance responses, breath rate, and breath rate variability (F1 = 0.82). Self-assessment measures indicated successful stress induction. {$\alpha$}-amylase and cortisol showed effect sizes of -0.78 and 0.55, respectively. In summary, the hypothalamic-pituitary-adrenocortical axis and sympathetic nervous system were successfully activated. Our findings facilitate a coherent and integrative understanding of the assessment of the stress response and help to align applications and future research concerning acute mental stress.},
langid = {english},
keywords = {Blood pressure,Cortisol,Electrocardiography,Heart rate,Psychological stress,Psychometrics,Saliva,Signal filtering},
file = {C:\Users\martin\Zotero\storage\8UFV4UEN\Ernst et al. - 2023 - Assessment of the human response to acute mental s.pdf}
}
  • [DOI] A. Hammer, H. Malberg, and M. Schmidt, “Cardiovascular Reflections of Sympathovagal Imbalance Precede the Onset of Atrial Fibrillation,” in 2023 Computing in Cardiology (CinC), 2023, p. 1–4.
    [Bibtex] 
    @inproceedings{hammer_cardiovascular_2023,
title = {Cardiovascular {{Reflections}} of {{Sympathovagal Imbalance Precede}} the {{Onset}} of {{Atrial Fibrillation}}},
booktitle = {2023 {{Computing}} in {{Cardiology}} ({{CinC}})},
author = {Hammer, Alexander and Malberg, Hagen and Schmidt, Martin},
year = {2023},
month = oct,
volume = {50},
pages = {1--4},
issn = {2325-887X},
doi = {10.22489/CinC.2023.399},
urldate = {2024-04-18},
abstract = {Sympathovagal imbalance is known to precede the on-set of atrial fibrillation (AF) and has been analyzed extensively based on heart rate variability (HRV). However, the relationship between sympathetic and vagal effects before AF onset and their influence on various HRV features have not been fully elucidated. QT interval variability (QTV) reflects sympathetic activity and may therefore provide further insights into this relationship. Using the time delay stability (TDS) method, we investigated temporal changes in coupling behavior before AF onset between 20 vagal or sympathovagal-associated HRV and QTV features. We applied the TDS method to 26 electrocardiograms from the MIT-BIH AF database with at least one hour of sinus rhythm preceding AF onset. Sinus rhythm segments were split into 5-minute windows with 50 \% overlap. Logistic regression analysis revealed significantly (p {$<$} 0.01) increased coupling between QTV and vagal HRV features from 20 to 15 minutes before AF onset. We found similar behavior between QTV and sympathovagal HRV features. This indicates sympathetic predominance increasing until 15 minutes before the onset of AF and decreasing towards vagal predominance right before AF onset. Our results provide new insights into temporal changes of sympathovagal imbalance preceding AF onset and may improve the prediction of AF in clinical applications.},
keywords = {Atrial fibrillation,Couplings,Databases,Delay effects,Logistic regression,Rhythm,Stability analysis},
file = {C\:\\Users\\martin\\Zotero\\storage\\SFVZEZQC\\Hammer et al. - 2023 - Cardiovascular Reflections of Sympathovagal Imbala.pdf;C\:\\Users\\martin\\Zotero\\storage\\HW23P6YW\\10363920.html}
}
  • [DOI] R. Hohmuth, H. Ernst, H. Malberg, and M. Schmidt, "Autonomic Regulation During Acute Mental Stress Is Characterized by Dynamic Interactions," in 2023 Computing in Cardiology (CinC), 2023, p. 1–4.
    [Bibtex] 
    @inproceedings{hohmuth_autonomic_2023,
title = {Autonomic {{Regulation During Acute Mental Stress Is Characterized}} by {{Dynamic Interactions}}},
booktitle = {2023 {{Computing}} in {{Cardiology}} ({{CinC}})},
author = {Hohmuth, Richard and Ernst, Hannes and Malberg, Hagen and Schmidt, Martin},
year = {2023},
month = oct,
volume = {50},
pages = {1--4},
issn = {2325-887X},
doi = {10.22489/CinC.2023.109},
urldate = {2024-04-18},
abstract = {The human organism can be understood as a complex system of dynamic interactions regulating physiological functions to maintain a state of homeostasis. Acute mental stress disrupts homeostasis and triggers a cardiovascular response controlled by the autonomic nervous system. We investigated the effects of acute mental stress on dynamic interactions between 20 vital parameters of haemodynamics, heart rate variability, QT variability, respiration, and skin conductance in 35 healthy subjects. To characterize dynamic interactions, we calculated symbolic transfer entropy between all vital parameters during baseline and acute mental stress. Significant changes were found in the dynamic interactions for 206 of 400 parameter combinations between baseline and acute mental stress (p {$<$} 0.05, Bonferoni-Holm corrected). Overall, dynamic interactions increased significantly by 9.3 \% (p {$<$} 0.001) compared to baseline. Specifically, acute mental stress caused a 22 \% increase of interactions between vital parameters that are dominated by sympathetic and parasympathetic nervous system. Our results indicate that acute mental stress leads to increased autonomic regulation. The characterization of dynamic interactions during acute mental stress provides insights for a better understanding of autonomic regulation processes.},
keywords = {Homeostasis,Human factors,Organisms,Physiology,Regulation,Skin,Task analysis},
file = {C\:\\Users\\martin\\Zotero\\storage\\G8PPHBYM\\Hohmuth et al. - 2023 - Autonomic Regulation During Acute Mental Stress Is.pdf;C\:\\Users\\martin\\Zotero\\storage\\JRAZSU58\\10363954.html}
}
  • [DOI] S. S. Shahrbabaki, D. Linz, S. Redline, K. Stone, K. Ensrud, and M. Baumert, "Sleep Arousal-Related Ventricular Repolarization Lability Is Associated With Cardiovascular Mortality in Older Community-Dwelling Men," Chest, vol. 163, iss. 2, p. 419–432, 2023.
    [Bibtex] 
    @article{shahrbabaki_sleep_2023,
title = {Sleep {{Arousal-Related Ventricular Repolarization Lability Is Associated With Cardiovascular Mortality}} in {{Older Community-Dwelling Men}}},
author = {Shahrbabaki, Sobhan Salari and Linz, Dominik and Redline, Susan and Stone, Katie and Ensrud, Kristine and Baumert, Mathias},
year = {2023},
month = feb,
journal = {Chest},
volume = {163},
number = {2},
pages = {419--432},
issn = {0012-3692},
doi = {10.1016/j.chest.2022.09.043},
urldate = {2024-04-18},
abstract = {Background Sleep is fragmented by brief arousals, and excessive arousal burden has been linked to increased cardiovascular (CV) risk, but mechanisms are poorly understood. Research Question Do arousals trigger cardiac ventricular repolarization lability that may predispose people to long-term cardiovascular mortality? Study Design and Methods This study analyzed 407,541 arousals in the overnight polysomnograms of 2,558 older men in the Osteoporotic Fractures in Men sleep study. QT and RR intervals were measured beat-to-beat starting 15~s prior to arousal onset until 15~s past onset. Ventricular repolarization lability was quantified by using the QT variability index (QTVi). Results During 10.1 {\textpm} 2.5 years of follow-up, 1,000 men died of any cause, including 348 CV deaths. During arousals, QT and RR variability increased on average by 5 and 55~ms, respectively, resulting in a paradoxical transient decrease in QTVi from 0.07 {\textpm} 1.68 to --1.00 {\textpm} 1.68. Multivariable Cox proportional hazards analysis adjusted for age, BMI, cardiovascular and respiratory risk factors, sleep-disordered breathing and arousal, diabetes, and Parkinson disease indicated that excessive QTVi during arousal was independently associated with all-cause and CV mortality (all-cause hazard ratio, 1.20 [95\%~CI, 1.04-1.38; P~= .012]; CV hazard ratio, 1.29 [95\%~CI, 1.01 -1.65; P~= .043]). Interpretation Arousals affect ventricular repolarization. A disproportionate increase in QT variability during arousal is associated with an increased all-cause and CV mortality and may reflect ventricular repolarization maladaptation to the arousal stimulus. Whether arousal-related QTVi can be used for more tailored risk stratification warrants further study, including evaluating whether arousal suppression attenuates ventricular repolarization lability and reduces subsequent mortality. Clinical Trial Registration ClinicalTrials.gov; No.: NCT00070681; URL: www.clinicaltrials.gov},
keywords = {all-cause mortality,cardiovascular mortality,QT variability index,sleep apnea,sleep arousal,ventricular repolarization},
file = {C\:\\Users\\martin\\Zotero\\storage\\6YSLR6US\\Shahrbabaki et al. - 2023 - Sleep Arousal-Related Ventricular Repolarization L.pdf;C\:\\Users\\martin\\Zotero\\storage\\CWYM4CCI\\S0012369222039228.html}
}

2022

  • [DOI] F. El-Hamad and M. Baumert, "Comparison of Single-Lead and Multi-Lead ECG for QT Variability Assessment Using Autoregressive Modelling," Physiological Measurement, vol. 43, iss. 10, p. 105002, 2022.
    [Bibtex] 
    @article{el-hamad_comparison_2022,
title = {Comparison of Single-Lead and Multi-Lead {{ECG}} for {{QT}} Variability Assessment Using Autoregressive Modelling},
author = {El-Hamad, Fatima and Baumert, Mathias},
year = {2022},
month = oct,
journal = {Physiological Measurement},
volume = {43},
number = {10},
pages = {105002},
publisher = {IOP Publishing},
issn = {0967-3334},
doi = {10.1088/1361-6579/ac92be},
urldate = {2022-12-05},
abstract = {Objective. Beat-to-beat fluctuations in the QT interval---QT variability (QTV)---have been shown to vary amongst the different ECG leads. This study aims to compare the utility of single and multi-lead ECG to disentangle the mechanisms contributing to QTV. Approach. Twelve-lead ECG was analysed in 57 coronary artery disease patients before and after an elective percutaneous transluminal coronary angiography (PTCA) procedure. QT, RR and respiration time series were extracted. QTV was decomposed into contributions by heart rate, respiration and QTV independent of heart rate and respiration using parametric autoregressive modelling. Signal-to-noise ratio, model goodness-of-fit, mean QT, corrected QT, QT variability and RR variability were also computed. Results from two single leads (Lead II and V5) and three one-dimensional representations of 12-lead ECG (principal component analysis (PCA), vector magnitude (VM), and root mean square of the 8 independent leads of the standard 12 leads (RMS8)) were compared during resting conditions, before and after PTCA, and between patients with myocardial infarction and those without. Main results. At baseline, mean QT and corrected QT were significantly lower in VM and RMS8 compared to single leads. While overall QT variability was not different between the leads, QT independent of heart rate and respiration was significantly lower in VM and RMS8. Following PTCA, changes in these variables were similar in all leads. Differences between patients with MI and those without MI were consistent in all leads. Significance. Despite the differences in some QTV components amongst various leads, single-lead ECG could be sufficient for analyzing QTV in populations with pathological cardiovascular conditions compared to those without, or for quantification of intervention effects.},
langid = {english},
file = {C:\Users\martin\Zotero\storage\6PAIPDLG\El-Hamad und Baumert - 2022 - Comparison of single-lead and multi-lead ECG for Q.pdf}
}
  • [DOI] A. Hammer, H. Malberg, and M. Schmidt, "Towards the Prediction of Atrial Fibrillation Using Interpretable ECG Features," in 2022 Computing in Cardiology (CinC), 2022, p. 1–4.
    [Bibtex] 
    @inproceedings{hammer_towards_2022,
title = {Towards the {{Prediction}} of {{Atrial Fibrillation Using Interpretable ECG Features}}},
booktitle = {2022 {{Computing}} in {{Cardiology}} ({{CinC}})},
author = {Hammer, Alexander and Malberg, Hagen and Schmidt, Martin},
year = {2022},
month = sep,
volume = {498},
pages = {1--4},
issn = {2325-887X},
doi = {10.22489/CinC.2022.236},
urldate = {2024-04-18},
abstract = {Atrial fibrillation (AF) is our society's most common cardiac arrhythmic disease, leading to increased morbidity and mortality. Predicting AF episodes during sinus rhythm based on electrocardiograms (ECGs) allows timely interventions. It is known, that changes in selected ECG morphology features are a predictor for the onset of AF, but no systematic investigation of different ECG features' temporal changes has been performed so far. We split sinus rhythm episodes of 60 minutes preceding AF from the MIT-BIH AF database into segments of 5 minutes with 50\% overlap (n=644) and calculated 155 features of different domains per segment. Logistic regression analyses between the segments preceding AF and others revealed the most significant effects for segments ending 5 minutes before AF onset, with PQ interval slope (p {$<$} 0.01), PQ interval correlation (p {$<$} 0.05), and median RR time (p {$<$} 0.05) being the most relevant features. A decision tree ensemble, trained with all features, achieved an accuracy of 0.87 when distinguishing 8 segment clusters. Our results confirm expected changes in ECG features (e.g., PQ interval) before AF episodes, indicating impaired atrial excitation, and show that the combination of interpretable features is sufficient to discriminate at different points in time before AF onset. For advanced analyses, more extensive databases should be included.},
keywords = {Atrial fibrillation,Correlation,Databases,Electrocardiography,Morphology,Rhythm,Systematics},
file = {C:\Users\martin\Zotero\storage\Q7DQCZVJ\Hammer et al. - 2022 - Towards the Prediction of Atrial Fibrillation Usin.pdf}
}
  • [DOI] S. S. Shahrbabaki and M. Baumert, "Assessment of the Cardiac Response to Sleep Arousal," in 6th Kuala Lumpur International Conference on Biomedical Engineering 2021, Cham, 2022, p. 593–600.
    [Bibtex] 
    @inproceedings{shahrbabaki_assessment_2022,
title = {Assessment of the {{Cardiac Response}} to {{Sleep Arousal}}},
booktitle = {6th {{Kuala Lumpur International Conference}} on {{Biomedical Engineering}} 2021},
author = {Shahrbabaki, Sobhan Salari and Baumert, Mathias},
editor = {Usman, Juliana and Liew, Yih Miin and Ahmad, Mohd Yazed and Ibrahim, Fatimah},
year = {2022},
series = {{{IFMBE Proceedings}}},
pages = {593--600},
publisher = {Springer International Publishing},
address = {Cham},
doi = {10.1007/978-3-030-90724-2_63},
abstract = {Sleep arousal or transient unconscious wakefulness is a part of normal sleep. However, once its frequency increases, it may disturb the sleep and make it fragmented. The objective of this study is to assess the effect of sleep arousals on cardiovascular function. We investigated cardiac responses to sleep arousal in a large sample comprising 2656 older men. We quantified beat-to-beat QT and RR time intervals on ECG 15~s prior and following to arousal onset. Obtained results show that in more than three-quarters of the men, the average RR interval shortened during arousal compared to pre-and post-arousal intervals, while less than half of the men experienced average QT interval shortening during arousals. The QT and RR variability increased significantly during arousal, where RR variability changes were more prominent than QT variability changes. The QT variability index was weakly correlated with the apnea--hypopnea index and arousal index. In conclusion, arousal episodes trigger cardiovascular function, and their effect can be measured and quantified through cardiac QT and RR time intervals.},
isbn = {978-3-030-90724-2},
langid = {english},
keywords = {Cardiac time interval,Heart rate,Polysomnography,QT variability,Sleep arousal},
file = {C:\Users\martin\Zotero\storage\3IIAD3FB\Shahrbabaki und Baumert - 2022 - Assessment of the Cardiac Response to Sleep Arousa.pdf}
}

2021

  • [DOI] A. Hammer, M. Scherpf, H. Ernst, J. Weiß, D. Schwensow, and M. Schmidt, "Automatic Classification of Full- and Reduced-Lead Electrocardiograms Using Morphological Feature Extraction," in 2021 Computing in Cardiology (CinC), 2021, p. 1–4.
    [Bibtex] 
    @inproceedings{hammer_automatic_2021,
title = {Automatic {{Classification}} of {{Full-}} and {{Reduced-Lead Electrocardiograms Using Morphological Feature Extraction}}},
booktitle = {2021 {{Computing}} in {{Cardiology}} ({{CinC}})},
author = {Hammer, Alexander and Scherpf, Matthieu and Ernst, Hannes and Wei{\ss}, Jonas and Schwensow, Daniel and Schmidt, Martin},
year = {2021},
month = sep,
volume = {48},
pages = {1--4},
issn = {2325-887X},
doi = {10.23919/CinC53138.2021.9662797},
abstract = {Cardiovascular diseases are the global leading cause of death. Automated electrocardiogram (ECG) analysis can support clinicians to identify abnormal excitation of the heart and prevent premature cardiovascular death. An explainable classification is particularly important for support systems. Our contribution to the PhysioNet/CinC Challenge 2021 (team name: ibmtPeakyFinders) therefore pursues an approach that is based on interpretable features to be as explainable as possible. To meet the challenge goal of developing an algorithm that works for both 12-lead and reduced lead ECGs, we processed each lead separately. We focused on signal processing techniques based on template delineation that yield the template's fiducial points to take the ECG waveform morphology into account. In addition to beat intervals and amplitudes obtained from the template, various heart rate variability and QT interval variability features were extracted and supplemented by signal quality indices. Our classification approach utilized a decision tree ensemble in a one-vs-rest approach. The model parameters were determined using an extensive grid search. Our approach achieved challenge scores of 0.47, 0.47, 0.34, 0.40, and 0.41 on hidden 12-, 6-, 3-, 4-, and 2-lead test sets, respectively, which corresponds to the ranks 12, 10, 23, 18, and 16 out of 39 teams.},
keywords = {Classification algorithms,Decision trees,Electrocardiography,Feature extraction,Heart,Heart rate variability,Lead,Morphology,Signal processing,Signal processing algorithms},
file = {C\:\\Users\\martin\\Zotero\\storage\\E5CA938T\\Hammer et al. - 2021 - Automatic Classification of Full- and Reduced-Lead.pdf;C\:\\Users\\martin\\Zotero\\storage\\G4YKIR8W\\9662797.html}
}
  • [DOI] F. Karisik and M. Baumert, "Template Adaptation of 2D Quasi-Periodic Data Using a Soft-Assign Localized Correspondence Matrix," IEEE Transactions on Signal Processing, vol. 69, p. 826–836, 2021.
    [Bibtex] 
    @article{karisik_template_2021,
title = {Template {{Adaptation}} of {{2D Quasi-Periodic Data Using}} a {{Soft-Assign Localized Correspondence Matrix}}},
author = {Karisik, Filip and Baumert, Mathias},
year = {2021},
journal = {IEEE Transactions on Signal Processing},
volume = {69},
pages = {826--836},
issn = {1941-0476},
doi = {10.1109/TSP.2020.3048256},
abstract = {In this work we propose a framework for the adaptation of arbitrary quasi-periodic time series. We parameterize and adapt data using traditional free form deformations. The method follows an alternating approach, inspired by the robust point matching algorithm, under which a correspondence matrix is updated and the subsequent deformation is obtained; thus, the template data are adapted to the target data. We demonstrate the performance of the algorithm across several electrocardiogram (ECG) and photoplethysmogram (PPG) databases and compare it to previous works.},
keywords = {electrocardiogram,Electrocardiography,grip-pull technique,Lattices,photoplethysmogram,registration,Shape,Signal processing,Signal processing algorithms,Strain,Template adaptation,Time series analysis},
file = {C\:\\Users\\martin\\Zotero\\storage\\3972MQCS\\Karisik und Baumert - 2021 - Template Adaptation of 2D Quasi-Periodic Data Usin.pdf;C\:\\Users\\martin\\Zotero\\storage\\ITK2JTW9\\9311750.html}
}
  • [DOI] M. Schmidt, F. Karisik, S. Zaunseder, A. Linke, H. Malberg, and M. Baumert, "Evaluation of Ventricular Repolarization Variability in Patients With Nonischemic Dilated Cardiomyopathy From Vectorcardiography," in 2021 Computing in Cardiology (CinC), 2021, p. 1–4.
    [Bibtex] 
    @inproceedings{schmidt_evaluation_2021,
title = {Evaluation of {{Ventricular Repolarization Variability}} in {{Patients With Nonischemic Dilated Cardiomyopathy From Vectorcardiography}}},
booktitle = {2021 {{Computing}} in {{Cardiology}} ({{CinC}})},
author = {Schmidt, Martin and Karisik, Filip and Zaunseder, Sebastian and Linke, Axel and Malberg, Hagen and Baumert, Mathias},
year = {2021},
month = sep,
volume = {48},
pages = {1--4},
issn = {2325-887X},
doi = {10.23919/CinC53138.2021.9662932},
abstract = {To investigate the predictive value of Ventricular repo-larization variability (VRV) in patients with nonischemic dilated cardiomyopathy, we analyzed the Defibrillator in Non-Ischemic Cardiomyopathy Treatment Evaluation trial (DEFINITE). The Telemetric and Holter ECG Warehouse (THEW) data set E-HOL-03-0401-017 comprises 393 recordings from 236 patients. All patients had a left ventricular ejection fraction \${$<$} 36\$ \% and were randomized to receiving standard medical therapy with or without an ICD. 24h-Holter 3-lead (Frank lead system) ECGs were performed at enrollment and after up to 5 years' follow-up. The all-cause mortality during the follow-up period was 4.8 \%. We analyzed three-dimensional variability of the T-loop and QT interval variability on a single lead basis by employing three-dimensional signals adaptation and two-dimensional signal warping, respectively, to quantify VRV. To assess the predictive value of VRV parameters, Kaplan-Meier survival curves of baseline Holter ECGs were calculated. Our results showed significant association to survival ( \$P {$<$} 0.01\$ by the log-rank test) for T wave amplitude corrected QT interval variability index (cQTVi) on single lead basis. Low cQTVi group showed no mortality for the entire observation period. We found no associations between cQTVi groups and patient-specific parameters.},
keywords = {Cardiology,Costs,Defibrillation,Electrocardiography,Indexes,Lead,Telemetry},
file = {C\:\\Users\\martin\\Zotero\\storage\\8XFNSPVU\\Schmidt et al. - 2021 - Evaluation of Ventricular Repolarization Variabili.pdf;C\:\\Users\\martin\\Zotero\\storage\\YEY2GEXA\\9662932.html}
}

2020

  • F. J. El-Hamad, S. Y. Bonabi, A. Müller, A. Steger, G. Schmidt, and M. Baumert, "Augmented Oscillations in QT Interval Duration Predict Mortality Post Myocardial Infarction Independent of Heart Rate," Frontiers in Physiology, vol. 11, 2020.
    [Bibtex] 
    @article{el-hamad_augmented_2020,
title = {Augmented {{Oscillations}} in {{QT Interval Duration Predict Mortality Post Myocardial Infarction Independent}} of {{Heart Rate}}},
author = {El-Hamad, Fatima J. and Bonabi, Safa Y. and M{\"u}ller, Alexander and Steger, Alexander and Schmidt, Georg and Baumert, Mathias},
year = {2020},
journal = {Frontiers in Physiology},
volume = {11},
issn = {1664-042X},
urldate = {2022-12-04},
abstract = {ObjectiveThis study seeks to decompose QT variability (QTV) into physiological sources and assess their role for risk stratification in patients post myocardial infarction (MI). We hypothesize that the magnitude of QTV that cannot be explained by heart rate or respiration carries important prognostic information.BackgroundElevated beat-to-beat QTV is predictive of cardiac mortality, but the underlying mechanisms, and hence its interpretation, remain opaque.MethodsWe decomposed the QTV of 895 patients post MI into contributions by heart rate, respiration, and unexplained sources.ResultsCox proportional hazard analysis demonstrates that augmented oscillations in QTV and their level of dissociation from heart rate are associated with a higher 5-year mortality rate (18.4\% vs. 4.7\%, p {$<$} 0.0001). In patients with left ventricular ejection fraction (LVEF) {$>$} 35\%, a higher QTV risk score was associated with a significantly higher 5-year mortality rate (16\% vs. 4\%, p {$<$} 0.0001). In patients with a GRACE score {$\geq$} 120, a higher QTV risk score was associated with a significantly higher 5-year mortality (25\% vs. 11\%, p {$<$} 0.001).ConclusionAugmented oscillations in QTV and discordance from heart rate, possibly indicative of excessive sympathetic outflow to the ventricular myocardium, predict high risk in patients post MI independent from established risk markers.Clinical Trial Registrationwww.ClinicalTrials.gov, identifier NCT00196274.},
file = {C:\Users\martin\Zotero\storage\JWFNWLSH\El-Hamad et al. - 2020 - Augmented Oscillations in QT Interval Duration Pre.pdf}
}
  • [DOI] M. Schmidt, R. Dunker, H. Malberg, and S. Zaunseder, "Quantification of Ventricular Repolarization Fluctuations in Patients With Myocardial Infarction," in 2020 Computing in Cardiology, 2020, p. 1–4.
    [Bibtex] 
    @inproceedings{schmidt_quantification_2020,
title = {Quantification of {{Ventricular Repolarization Fluctuations}} in {{Patients With Myocardial Infarction}}},
booktitle = {2020 {{Computing}} in {{Cardiology}}},
author = {Schmidt, M. and Dunker, R. and Malberg, H. and Zaunseder, S.},
year = {2020},
month = sep,
pages = {1--4},
issn = {2325-887X},
doi = {10.22489/CinC.2020.168},
abstract = {The objective of this study was to quantify ventricular repolarization fluctuations in patients with myocardial infarction (MI) by a novel ECG waveform morphology based QT interval variability (QTV) measure. We analyzed recordings of 79 MI patients and 69 healthy control subjects included in the Physikalisch-Technische Bunde-sanstalt diagnostic ECG database. To characterize the QT interval waveform, we employed two-dimensional signal warping (2DSW). Based on the two-dimensional template adaptation to every beat, a novel parameter QTfluc has been developed to take into account complex QT interval's waveform fluctuations in time and amplitude. To demonstrate the power of QTfluc we (1) compared MI patients and healthy subjects and (2) examined the stability of various QTV measures including QTfluc in relation to QT interval boundary shifts. A comparison of QTfluc with standard QTV measures showed a significant improvement (ef-fect size increased up to 60 \%) in discriminating between MI patients and healthy subjects. QT interval boundary shifts showed significant less impact (by factor 10) on the stability of QTfluc in comparison to standard QTV measures. The proposed measure showed significant improved characterization of ventricular repolarization lability in MI patients. Moreover, QTfluc showed more stable characteristics and is less dependent on QT interval boarders.},
keywords = {Electrocardiography,Fluctuations,Myocardium,Power measurement,Size measurement,Stability analysis,Standards},
file = {C\:\\Users\\martin\\Zotero\\storage\\W9GLNZBR\\Schmidt et al. - 2020 - Quantification of Ventricular Repolarization Fluct.pdf;C\:\\Users\\martin\\Zotero\\storage\\B2QYU2LI\\9344341.html}
}
  • [DOI] J. Weiß, H. Malberg, and M. Schmidt, "Detection Quality Indices for Improved Heart Beat Assessment in Non-Invasive Fetal ECG," in 2020 Computing in Cardiology, 2020, p. 1–4.
    [Bibtex] 
    @inproceedings{weis_detection_2020,
title = {Detection {{Quality Indices}} for {{Improved Heart Beat Assessment}} in {{Non-Invasive Fetal ECG}}},
booktitle = {2020 {{Computing}} in {{Cardiology}}},
author = {Wei{\ss}, Jonas and Malberg, Hagen and Schmidt, Martin},
year = {2020},
month = sep,
pages = {1--4},
issn = {2325-887X},
doi = {10.22489/CinC.2020.231},
abstract = {In this work, we establish the novel concept of detection quality indices (DQI) for the assessment of non-invasive fetal heartbeat detections. We grouped the DQIs in four categories concerning the detection properties they address and used these DQIs as features to classify correct detections and two detection errors with a decision tree. Our classifier was able to distinguish between correct detection and two detection errors (f1 = 0.90). By excluding the detection errors, we were able to improve the error of time-domain heart rate variability parameters and approximated entropy compared to manual detection by 35 percentage points on average in a first clinical test setting.},
keywords = {Electrocardiography,Entropy,Feature extraction,Heart beat,Heart rate variability,Manuals,Time-domain analysis},
file = {C\:\\Users\\martin\\Zotero\\storage\\UY39Q4VQ\\Weiß et al. - 2020 - Detection Quality Indices for Improved Heart Beat .pdf;C\:\\Users\\martin\\Zotero\\storage\\JMDHB255\\9344354.html}
}

2019

  • F. El-Hamad, S. Y. Bonabi, A. Muller, A. Steger, G. Schmidt, and M. Baumert, "QT Interval Variability Independent of Heart Rate Predicts Mortality Post Myocardial Infarction," in 2019 Computing in Cardiology Conference (CinC), Singapore, 2019.
    [Bibtex] 
    @inproceedings{el-hamad_qt_2019,
title = {{{QT Interval Variability Independent}} of {{Heart Rate Predicts Mortality Post Myocardial Infarction}}},
booktitle = {2019 {{Computing}} in {{Cardiology Conference}} ({{CinC}})},
author = {El-Hamad, Fatima and Bonabi, Safa Yaghini and Muller, Alexander and Steger, Alexander and Schmidt, Georg and Baumert, Mathias},
year = {2019},
month = sep,
address = {Singapore}
}
  • [DOI] F. El-Hamad, M. Javorka, B. Czippelova, J. Krohova, Z. Turianikova, A. Porta, and M. Baumert, "Repolarization Variability Independent of Heart Rate during Sympathetic Activation Elicited by Head-up Tilt," Medical & Biological Engineering & Computing, vol. 57, iss. 8, p. 1753–1762, 2019.
    [Bibtex] 
    @article{el-hamad_repolarization_2019,
title = {Repolarization Variability Independent of Heart Rate during Sympathetic Activation Elicited by Head-up Tilt},
author = {El-Hamad, Fatima and Javorka, Michal and Czippelova, Barbora and Krohova, Jana and Turianikova, Zuzana and Porta, Alberto and Baumert, Mathias},
year = {2019},
month = aug,
journal = {Medical \& Biological Engineering \& Computing},
volume = {57},
number = {8},
pages = {1753--1762},
issn = {1741-0444},
doi = {10.1007/s11517-019-01998-9},
urldate = {2019-11-13},
abstract = {The fraction of repolarization variability independent of RR interval variability is of clinical interest. It has been linked to direct autonomic nervous system (ANS) regulation of the ventricles in healthy subjects and seems to reflect the instability of the ventricular repolarization process in heart disease. In this study, we sought to identify repolarization measures that best reflect the sympathetic influences on the ventricles independent of the RR interval. ECG was recorded in 46 young subjects during supine and then following 45 degrees head-up tilt. RR intervals and five repolarization features (QTend, QTpeak, RTend, RTpeak, and TpTe) were extracted from the ECG recordings. Repolarization variability was separated into RR-dependent and RR-independent variability using parametric spectral analysis. Results show that LF power of TpTe is independent of RR in both supine and tilt, while the LF power of QTend and RTend independent of RR and respiration increases following tilt. We conclude that TpTe is independent of RR and is highly affected by respiration. QTend and RTend LF power might reflect the sympathetic influences on the ventricles elicited by tilt. Open image in new window Graphical abstract},
langid = {english},
keywords = {Autonomic nervous system,Head-up tilt,Heart rate variability,QT interval,Repolarization,Sympathetic activation,Tpeak-Tend},
file = {C:\Users\martin\Zotero\storage\5D38DTA4\El-Hamad et al. - 2019 - Repolarization variability independent of heart ra.pdf}
}
  • [DOI] F. Karisik, M. Schmidt, and M. Baumert, "Beat-to-Beat Analysis of Vectorcardiogram by Inhomogeneous Template Adaptation," in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019, p. 83–86.
    [Bibtex] 
    @inproceedings{karisik_beat--beat_2019,
title = {Beat-to-{{Beat Analysis}} of {{Vectorcardiogram}} by {{Inhomogeneous Template Adaptation}}},
booktitle = {2019 41st {{Annual International Conference}} of the {{IEEE Engineering}} in {{Medicine}} and {{Biology Society}} ({{EMBC}})},
author = {Karisik, Filip and Schmidt, Martin and Baumert, Mathias},
year = {2019},
month = jul,
pages = {83--86},
issn = {1558-4615, 1557-170X},
doi = {10.1109/EMBC.2019.8857436},
abstract = {Increased beat-to-beat QT interval variability in electrocardiograms is a robust descriptor of ventricular depolarization and repolarization lability. Variability analysis of the depolarization and repolarization intervals in vectorcardiogram has indicated potential diagnostic abilities. Here, we describe an inhomogeneous signal adaptation technique for vectorcardiogram. We propose a novel global-to-local adaptation method that yields robust results even when dealing with noisy vectorcardiogram signals. We evaluated several vectorcardiogram features using the proposed adaptation technique on the PTB database to demonstrate its potential diagnostic prowess for myocardial infarction.},
keywords = {Databases,Electrocardiography,Estimation,Kernel,Myocardium,Nonhomogeneous media,Shape},
file = {C\:\\Users\\martin\\Zotero\\storage\\F95XQAJY\\Karisik et al. - 2019 - Beat-to-Beat Analysis of Vectorcardiogram by Inhom.pdf;C\:\\Users\\martin\\Zotero\\storage\\W585NHUX\\8857436.html}
}
  • [DOI] F. Karisik and M. Baumert, "Inhomogeneous Template Adaptation of Temporal Quasi-Periodic Three-Dimensional Signals," IEEE Transactions on Signal Processing, vol. 67, iss. 23, p. 6067–6077, 2019.
    [Bibtex] 
    @article{karisik_inhomogeneous_2019,
title = {Inhomogeneous {{Template Adaptation}} of {{Temporal Quasi-Periodic Three-Dimensional Signals}}},
author = {Karisik, Filip and Baumert, Mathias},
year = {2019},
month = dec,
journal = {IEEE Transactions on Signal Processing},
volume = {67},
number = {23},
pages = {6067--6077},
issn = {1053-587X, 1941-0476},
doi = {10.1109/TSP.2019.2951229},
urldate = {2019-12-02}
}
  • [DOI] F. Karisik and M. Baumert, "A Long Short-Term Memory Network to Classify Myocardial Infarction Using Vectorcardiographic Ventricular Depolarization and Repolarization," in 2019 Computing in Cardiology (CinC), 2019, p. Page 1-Page 4.
    [Bibtex] 
    @inproceedings{karisik_long_2019,
title = {A {{Long Short-Term Memory Network}} to {{Classify Myocardial Infarction Using Vectorcardiographic Ventricular Depolarization}} and {{Repolarization}}},
booktitle = {2019 {{Computing}} in {{Cardiology}} ({{CinC}})},
author = {Karisik, Filip and Baumert, Mathias},
year = {2019},
month = sep,
pages = {Page 1-Page 4},
issn = {2325-887X},
doi = {10.22489/CinC.2019.272},
abstract = {QT interval beat-to-beat variability has indicated diag-nostic/prognostic abilities in myocardial infarction. Furthermore, research has suggested that vectorcardiography has superior diagnostic abilities compared to the standard electrocardiogram in myocardial infarction. This study aimed to assess the ability of vectorcardiographic ventricular depolarization and repolarization to classify myocardial infarction patients versus control subjects. 147 vectorcardiogram recordings (78 MI vs. 69 Control) were obtained from the PTB database. For each recording, 60 QRS-complex and T-wave VCG beats were extracted using the Two-Dimensional Signal Warping algorithm. An inhomogeneous three-dimensional template adaptation scheme was applied on each QRS-loop and T-loop to capture subtle morphological changes from beat-to-beat. Training was performed on a regularized three-layer long short-term memory network. The classifier produced test set classification results with an overall 89.1\% accuracy, 89.1\% sensitivity and 90.0\% specificity. In conclusion, high classification accuracy has been achieved on a relatively small subset of the PTB database. Future work will look to improve the classification results by extending the analysis across the entire PTB database.},
keywords = {Databases,Electrocardiography,Kernel,Myocardium,Nonhomogeneous media,Sensitivity,Strain},
file = {C\:\\Users\\martin\\Zotero\\storage\\YAQYRW47\\Karisik und Baumert - 2019 - A Long Short-Term Memory Network to Classify Myoca.pdf;C\:\\Users\\martin\\Zotero\\storage\\23G8LU4U\\9005836.html}
}
  • [DOI] M. Schmidt, M. Baumert, H. Malberg, and S. Zaunseder, "Sex Differences in Nocturnal Ventricular Repolarization Variability," in 2019 Computing in Cardiology Conference (CinC), Singapore, 2019.
    [Bibtex] 
    @inproceedings{schmidt_sex_2019,
title = {Sex {{Differences}} in {{Nocturnal Ventricular Repolarization Variability}}},
booktitle = {2019 {{Computing}} in {{Cardiology Conference}} ({{CinC}})},
author = {Schmidt, Martin and Baumert, Mathias and Malberg, Hagen and Zaunseder, Sebastian},
year = {2019},
month = dec,
address = {Singapore},
doi = {10.22489/CinC.2019.069}
}
  • [DOI] S. S. Shahrbabaki and M. Baumert, "Sleep Arousal and Sudden Changes in Cardiac QT Interval," in 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019, p. 3658–3661.
    [Bibtex] 
    @inproceedings{shahrbabaki_sleep_2019,
title = {Sleep {{Arousal}} and {{Sudden Changes}} in {{Cardiac QT Interval}}},
booktitle = {2019 41st {{Annual International Conference}} of the {{IEEE Engineering}} in {{Medicine}} and {{Biology Society}} ({{EMBC}})},
author = {Shahrbabaki, Sobhan Salari and Baumert, Mathias},
year = {2019},
month = jul,
pages = {3658--3661},
issn = {1558-4615, 1557-170X},
doi = {10.1109/EMBC.2019.8857651},
abstract = {Sleep arousal is generally defined as an abrupt shift in EEG frequency with a duration of 3-16 seconds. Arousal from sleep expected to cause sudden changes in the cardiovascular system that can manifest as cardiac responses. In this paper, our objective was to investigate how cardiac characteristics change due to arousal. We focused on the QT interval fluctuations in ECG during the occurrence of arousals. We analysed 7373 sleep arousals collected from 50 males that were older than 65 years. We analysed the ECG signal 5 seconds prior to and 10 seconds after each arousal onset (Pre and Post-Onset). Q and T waves were detected for all Pre and Post-Onset windows to estimate their time intervals. To find out whether the QT interval, a marker of ventricular activation, is modulated by arousal onset, we have applied graphical and statistical analysis. Our observations indicate that in 47 out of 50 subjects (94\%), the average QT interval of all arousal significantly shortened at arousal onset. We observed similar outcomes for different types of arousals, indicating that the shortening in average QT interval is independent of the type of arousal. We also studied the relative QT interval change during arousal. The distribution of relative QT interval changes demonstrates that around 60\% of arousals increase or decrease QT interval by a maximum of 20\%. The probability of QT time interval shortening was twice that of QT interval lengthening.},
keywords = {Correlation,Electrocardiography,Electroencephalography,Heart rate,Microsoft Windows,Resonant frequency,Sleep},
file = {C\:\\Users\\martin\\Zotero\\storage\\6AGZUCGU\\Shahrbabaki und Baumert - 2019 - Sleep Arousal and Sudden Changes in Cardiac QT Int.pdf;C\:\\Users\\martin\\Zotero\\storage\\SYECBTVJ\\8857651.html}
}
  • Z. Zaunseder, A. Trumpp, H. Malberg, and M. Schmidt, "Verfahren zur Bestimmung eines physiologischen Parameters sowie Verfahren zur Bestimmung des Blutdruckes unter Berücksichtigung des physiologischen Parameters," , iss. DE102017126551B4, 2019.
    [Bibtex] 
    @patent{zaunseder_verfahren_2019,
title = {{Verfahren zur Bestimmung eines physiologischen Parameters sowie Verfahren zur Bestimmung des Blutdruckes unter Ber{\"u}cksichtigung des physiologischen Parameters}},
author = {Zaunseder, Zaunseder and Trumpp, Alexander and Malberg, Hagen and Schmidt, Martin},
year = {2019},
month = nov,
number = {DE102017126551B4},
assignee = {Technische Universit{\"a}t Dresden, 01069 Dresden, DE},
langid = {ngerman},
nationality = {DE},
annotation = {rechtskr{\"a}ftig erteilt}
}

2018

  • [DOI] M. Schmidt, M. Baumert, H. Malberg, and S. Zaunseder, "Iterative Two-Dimensional Signal Warping–-Towards a Generalized Approach for Adaption of One-Dimensional Signals," Biomedical Signal Processing and Control, vol. 43, p. 311–319, 2018.
    [Bibtex] 
    @article{schmidt_iterative_2018,
title = {Iterative Two-Dimensional Signal Warping---{{Towards}} a Generalized Approach for Adaption of One-Dimensional Signals},
author = {Schmidt, Martin and Baumert, Mathias and Malberg, Hagen and Zaunseder, Sebastian},
year = {2018},
month = may,
journal = {Biomedical Signal Processing and Control},
volume = {43},
pages = {311--319},
issn = {1746-8094},
doi = {10.1016/j.bspc.2018.03.016},
urldate = {2018-04-03},
abstract = {The assessment of subtle morphological changes in noisy signals is a common challenge in the field of biomedical signal processing. Concerning the electrocardiogram (ECG), it may yield novel risk factors for cardiac mortality. Here, we describe an iterative two-dimensional signal warping algorithm (i2DSW), which morphological analyses even in case of noise ratios. i2DSW adapts a generalized iterative template adaptation process that yields a more flexible template and allows for better fitting of subtle variations of signal shapes. Moreover, the template segmentation is not dependent on signal morphology. We test its performance, by measuring beat-to-beat repolarization variability in simulated and clinical ECG. Simulation studies show higher robustness of i2DSW in presence of typical ECG artefacts compared to previously proposed methods including the existing two-dimensional warping technique (26\% improvement). Comparison of short-term ECG recorded in normal subjects versus patients with myocardial infarction (MI) confirmed increased repolarization variability in MI patients (p\,\<\,0.0001). Results obtained with long-term ECG show improved waveform adaptation of i2DSW (overall 19\%, up to 33\%). The assessment of subtle morphological changes by i2DSW may yield novel and more robust risk factors for cardiac mortality. By avoiding a fixed template segmentation, the generalized design of i2DSW has the potential to be also powerful in the application to other quasi-periodic signals.},
keywords = {2DSW,ECG,i2DSW,QT interval,QT variability,Warping},
file = {C\:\\Users\\martin\\Zotero\\storage\\YEVSWUAU\\Schmidt et al. - 2018 - Iterative two-dimensional signal warping—Towards a.pdf;C\:\\Users\\martin\\Zotero\\storage\\FD9Q2M38\\S1746809418300740.html}
}
  • [DOI] M. Schmidt, M. Baumert, T. Penzel, H. Malberg, and S. Zaunseder, "Nocturnal Ventricular Repolarization Lability Predicts Cardiovascular Mortality in the Sleep Heart Health Study," American Journal of Physiology-Heart and Circulatory Physiology, vol. 316, iss. 3, p. H495-H505, 2018.
    [Bibtex] 
    @article{schmidt_nocturnal_2018,
title = {Nocturnal Ventricular Repolarization Lability Predicts Cardiovascular Mortality in the {{Sleep Heart Health Study}}},
author = {Schmidt, Martin and Baumert, Mathias and Penzel, Thomas and Malberg, Hagen and Zaunseder, Sebastian},
year = {2018},
month = dec,
journal = {American Journal of Physiology-Heart and Circulatory Physiology},
volume = {316},
number = {3},
pages = {H495-H505},
issn = {0363-6135},
doi = {10.1152/ajpheart.00649.2018},
urldate = {2019-02-13},
abstract = {The objective of the present study was to quantify repolarization lability and its association with sex, sleep stage, and cardiovascular mortality. We analyzed polysomnographic recordings of 2,263 participants enrolled in the Sleep Heart Health Study (SHHS-2). Beat-to-beat QT interval variability (QTV) was quantified for consecutive epochs of 5 min according to the dominant sleep stage [wakefulness, nonrapid eye movement stage 2 (NREM2), nonrapid eye movement stage 3 (NREM3), and rapid eye movement (REM)]. To explore the effect of sleep stage and apnea-hypopnea index (AHI) on QT interval parameters, we used a general linear mixed model and mixed ANOVA. The Cox proportional hazards model was used for cardiovascular disease (CVD) death prediction. Sex-related differences in T wave amplitude (P {$<$} 0.001) resulted in artificial QTV differences. Hence, we corrected QTV parameters by T wave amplitude for further analysis. Sleep stages showed a significant effect (P {$<$} 0.001) on QTV. QTV was decreased in deep sleep compared with wakefulness, was higher in REM than in NREM, and showed a distinct relation to AHI in all sleep stages. The T wave amplitude-corrected QTV index (cQTVi) in REM sleep was predictive of CVD death (hazard ratio: 2.067, 95\% confidence interval: 1.105--3.867, P {$<$} 0.05) in a proportional hazards model. We demonstrated a significant impact of sleep stages on ventricular repolarization variability. Sex differences in QTV are due to differences in T wave amplitude, which should be corrected for. Independent characteristics of QTV measures to sleep stages and AHI showed different behaviors of heart rate variability and QTV expressed as cQTVi. cQTVi during REM sleep predicts CVD death.NEW \& NOTEWORTHY We demonstrate here, for the first time, a significant impact of sleep stages on ventricular repolarization variability, quantified as QT interval variability (QTV). We showed that QTV is increased in rapid eye movement sleep, reflective of high sympathetic drive, and predicts death from cardiovascular disease. Sex-related differences in QTV are shown to be owing to differences in T wave amplitude, which should be corrected for.},
file = {C\:\\Users\\martin\\Zotero\\storage\\ZB2VCUM6\\Schmidt et al. - 2018 - Nocturnal ventricular repolarization lability pred.pdf;C\:\\Users\\martin\\Zotero\\storage\\5PZP78R6\\ajpheart.00649.html}
}

2017

  • [DOI] M. Baumert, "Beat-to-Beat QT Interval Variability and Autonomic Activity," in ECG Time Series Variability Analysis, 1 ed., H. F. Jelinek, D. J. Cornforth, and A. H. Khandoker, Eds., Boca Raton: CRC Press, 2017, p. 403–412.
    [Bibtex] 
    @incollection{baumert_beat--beat_2017,
title = {Beat-to-{{Beat QT Interval Variability}} and {{Autonomic Activity}}},
booktitle = {{{ECG Time Series Variability Analysis}}},
author = {Baumert, Mathias},
editor = {Jelinek, Herbert F. and Cornforth, David J. and Khandoker, Ahsan H.},
year = {2017},
month = sep,
series = {Engineering and {{Medicine}}},
edition = {1},
pages = {403--412},
publisher = {CRC Press},
address = {Boca Raton},
doi = {10.4324/9781315372921-20},
urldate = {2019-01-30},
abstract = {The QT interval of a body surface electrocardiogram (ECG) reflects the depolarization and repolarization processes across the ventricular myocardium 20.2.},
isbn = {978-1-4822-4347-5},
langid = {english},
file = {C:\Users\martin\Zotero\storage\EGQG773U\9781315372921-20.html}
}

2016

  • [DOI] M. Baumert, M. Schmidt, S. Zaunseder, and A. Porta, "Effects of ECG Sampling Rate on QT Interval Variability Measurement," Biomedical Signal Processing and Control, vol. 25, iss. Supplement C, p. 159–164, 2016.
    [Bibtex] 
    @article{baumert_effects_2016,
title = {Effects of {{ECG}} Sampling Rate on {{QT}} Interval Variability Measurement},
author = {Baumert, Mathias and Schmidt, Martin and Zaunseder, Sebastian and Porta, Alberto},
year = {2016},
month = mar,
journal = {Biomedical Signal Processing and Control},
volume = {25},
number = {Supplement C},
pages = {159--164},
issn = {1746-8094},
doi = {10.1016/j.bspc.2015.11.011},
urldate = {2017-12-15},
abstract = {Beat-to-beat variability of the QT interval (QTV) has been used as a marker of repolarization lability and sympathetic activation. The aim of this study was to establish ECG sampling rate requirements for reliable QT interval variability measurement. We measured QTV in high resolution simulated (1000Hz) and real ECG (1600Hz; in the supine position during rest and during sympathetic activation upon standing), using time and frequency domain metrics as well as measures of symbolic dynamics for complexity assessment. We successively halved the sampling rate and investigated its effect on the QTV metrics. Reduction in sampling rate below 400Hz and 500Hz, respectively, resulted in a significant overestimation of QTV variability and also affected complexity measurement of QTV. QTV increased during standing compared to the supine measurement. At 100Hz, the posture related change in QTV was completely masked by the measurement noise introduced by the low sampling rate. In conclusion, ECG sampling rates of 500Hz yields a reliable QTV measurement, while sampling rates of 200Hz and below should be avoided.},
keywords = {ECG,QT interval,Sampling rate},
file = {C\:\\Users\\martin\\Zotero\\storage\\FNRHHRQV\\Baumert et al. - 2016 - Effects of ECG sampling rate on QT interval variab.pdf;C\:\\Users\\martin\\Zotero\\storage\\KTG83Q7R\\Baumert et al. - 2016 - Effects of ECG sampling rate on QT interval variab.pdf;C\:\\Users\\martin\\Zotero\\storage\\HVRFX9R6\\S1746809415001962.html;C\:\\Users\\martin\\Zotero\\storage\\NQV5XCV6\\S1746809415001962.html;C\:\\Users\\martin\\Zotero\\storage\\RCMR79G7\\S1746809415001962.html}
}
  • [DOI] M. Baumert, "Measurement of T Wave Variability in Body Surface ECG," Journal of Electrocardiology, vol. 49, iss. 6, p. 883–886, 2016.
    [Bibtex] 
    @article{baumert_measurement_2016,
title = {Measurement of {{T}} Wave Variability in Body Surface {{ECG}}},
author = {Baumert, Mathias},
year = {2016},
month = nov,
journal = {Journal of Electrocardiology},
volume = {49},
number = {6},
pages = {883--886},
issn = {0022-0736},
doi = {10.1016/j.jelectrocard.2016.07.014},
urldate = {2017-09-30},
abstract = {Lability in the ventricular repolarization process has been associated with an increased risk of experiencing ventricular tachycardia or fibrillation. A number of risk predictors have been devised that quantify beat-to-beat variability in the T wave morphology of body surface ECG. Initial studies have suggested that measurement of T wave variability may yield important prognostics markers of cardiac mortality, but approaches and experimental designs vary. The aim of this contribution is to provide an overview of existing techniques as well as discuss some of the methodical considerations.},
keywords = {ECG,Repolarization,T wave variability},
file = {C:\Users\martin\Zotero\storage\4JQ8FTLY\S0022073616300929.html}
}
  • [DOI] S. Y. Bonabi, F. El-Hamad, A. Müller, M. Dommasch, A. Steger, Georg Schmidt, and M. Baumert, "Recording Duration and Short-Term Reproducibility of Heart Rate and QT Interval Variability in Patients with Myocardial Infarction," Physiological Measurement, vol. 37, iss. 11, p. 1925, 2016.
    [Bibtex] 
    @article{bonabi_recording_2016,
title = {Recording Duration and Short-Term Reproducibility of Heart Rate and {{QT}} Interval Variability in Patients with Myocardial Infarction},
author = {Bonabi, Safa Yaghini and El-Hamad, Fatima and M{\"u}ller, Alexander and Dommasch, Michael and Steger, Alexander and {Georg Schmidt} and Baumert, Mathias},
year = {2016},
journal = {Physiological Measurement},
volume = {37},
number = {11},
pages = {1925},
issn = {0967-3334},
doi = {10.1088/0967-3334/37/11/1925},
urldate = {2017-11-04},
abstract = {Beat-to-beat variability of the QT interval (QTV) measured on surface ECG has emerged as a potential marker for ventricular repolarization instability and has been used along with heart rate variability (HRV) to predict arrhythmic risk. Since measurement modalities of QTV have not been standardized, the objective of this study was to investigate the effect of ECG recording duration on QTV as well as HRV. Using a database of 30 min ECG recorded from 500 patients with acute myocardial infraction during rest, we extracted RR and QT interval time series and estimated different HRV and QTV metrics over windows of varying length. Analysis of variance (ANOVA) and intra-class correlation analyses were computed to investigate the effect of recording length on consistency and short-term reproducibility of HRV and QTV variables. Good consistency (non-significant ANOVA results) and short-term reproducibility (intra-class correlation coefficients {$>$}0.8) were demonstrated for all but standard deviation based metrics when at least 200 beats were included in the estimation. In conclusion, QTV can be quantified from resting ECG with good short-term consistency and reproducibility that is comparable to that of HRV.},
langid = {english}
}
  • [DOI] M. Schmidt, M. Baumert, H. Malberg, and S. Zaunseder, "T Wave Amplitude Correction of QT Interval Variability for Improved Repolarization Lability Measurement," Frontiers in Physiology, vol. 7, 2016.
    [Bibtex] 
    @article{schmidt_t_2016,
title = {T {{Wave Amplitude Correction}} of {{QT Interval Variability}} for {{Improved Repolarization Lability Measurement}}},
author = {Schmidt, Martin and Baumert, Mathias and Malberg, Hagen and Zaunseder, Sebastian},
year = {2016},
journal = {Frontiers in Physiology},
volume = {7},
issn = {1664-042X},
doi = {10.3389/fphys.2016.00216},
urldate = {2017-09-30},
abstract = {Objectives: The inverse relationship between QT interval variability (QTV) and T wave amplitude potentially confounds QT variability assessment. We quantified the influence of the T wave amplitude on QTV in a comprehensive dataset and devised a correction formula. Methods: Three ECG datasets of healthy subjects were analyzed to model the relationship between T wave amplitude and QTV. To derive a generally valid correction formula, linear regression analysis was used. The proposed correction formula was applied to patients enrolled in the Evaluation of Defibrillator in Non-Ischemic Cardiomyopathy Treatment Evaluation trial (DEFINITE) to assess the prognostic significance of QTV for all-cause mortality in patients with non-ischemic dilated cardiomyopathy. Results: A strong inverse relationship between T wave amplitude and QTV was demonstrated, both in healthy subjects (R{$^2$} = 0.68, p {$<$} 0.001) and DEFINITE patients (R{$^2$} = 0.20, p {$<$} 0.001). Applying the T wave amplitude correction to QTV achieved 2.5-times better group discrimination between patients enrolled in the DEFINITE study and healthy subjects. Kaplan-Meier estimator analysis showed that T wave amplitude corrected QTVi is inversely related to survival (p {$<$} 0.01) and a significant predictor of all-cause mortality. Conclusion: We have proposed a simple correction formula for improved QTV assessment. Using this correction, predictive value of QTV for all-cause mortality in patients with non-ischemic cardiomyopathy has been demonstrated.},
langid = {english},
keywords = {Definite,ECG,QT interval variability,risk stratification,T wave amplitude},
annotation = {00006}
}

2015

  • [DOI] F. El-Hamad, E. Lambert, D. Abbott, and M. Baumert, "Relation between QT Interval Variability and Muscle Sympathetic Nerve Activity in Normal Subjects," American Journal of Physiology - Heart and Circulatory Physiology, vol. 309, iss. 7, p. H1218-H1224, 2015.
    [Bibtex] 
    @article{el-hamad_relation_2015,
title = {Relation between {{QT}} Interval Variability and Muscle Sympathetic Nerve Activity in Normal Subjects},
author = {El-Hamad, Fatima and Lambert, Elisabeth and Abbott, Derek and Baumert, Mathias},
year = {2015},
month = oct,
journal = {American Journal of Physiology - Heart and Circulatory Physiology},
volume = {309},
number = {7},
pages = {H1218-H1224},
issn = {0363-6135, 1522-1539},
doi = {10.1152/ajpheart.00230.2015},
urldate = {2017-09-30},
abstract = {Beat-to-beat variability of the QT interval (QTV) is sought to provide an indirect noninvasive measure of sympathetic nerve activity, but a formal quantification of this relationship has not been provided. In this study we used power contribution analysis to study the relationship between QTV and muscle sympathetic nerve activity (MSNA). ECG and MSNA were recorded in 10 healthy subjects in the supine position and after 40{$^\circ$} head-up tilt. Power spectrum analysis was performed using a linear autoregressive model with two external inputs: heart period (RR interval) variability (RRV) and MSNA. Total and low-frequency power of QTV was decomposed into contributions by RRV, MSNA, and sources independent of RRV and MSNA. Results show that the percentage of MSNA power contribution to QT is very small and does not change with tilt. RRV power contribution to QT power is notable and decreases with tilt, while the greatest percentage of QTV is independent of RRV and MSNA in the supine position and after 40{$^\circ$} head-up tilt. In conclusion, beat-to-beat QTV in normal subjects does not appear to be significantly affected by the rhythmic modulations in MSNA following low to moderate orthostatic stimulation. Therefore, MSNA oscillations may not represent a useful surrogate for cardiac sympathetic nerve activity at moderate levels of activation, or, alternatively, sympathetic influences on QTV are complex and not quantifiable with linear shift-invariant autoregressive models.},
copyright = {Copyright {\copyright} 2015 the American Physiological Society},
langid = {english},
pmid = {26276814},
file = {C\:\\Users\\martin\\Zotero\\storage\\AYSJWUPS\\El-Hamad et al. - 2015 - Relation between QT interval variability and muscl.pdf;C\:\\Users\\martin\\Zotero\\storage\\NW3JRAIP\\H1218.html}
}
  • M. Schmidt, M. Kircher, A. Noack, H. Malberg, and S. Zaunseder, "Challenges to QT Interval Variability Analysis in Mobile Applications," in Cardiovascular Mobile Health Conference, Tabarz, 2015.
    [Bibtex] 
    @inproceedings{schmidt_challenges_2015,
title = {Challenges to {{QT Interval Variability Analysis}} in {{Mobile Applications}}},
booktitle = {Cardiovascular {{Mobile Health Conference}}},
author = {Schmidt, Martin and Kircher, Marco and Noack, Alexander and Malberg, Hagen and Zaunseder, Sebastian},
year = {2015},
month = sep,
address = {Tabarz},
urldate = {2019-02-15},
langid = {english},
file = {C\:\\Users\\martin\\Zotero\\storage\\ITLQJSBG\\Schmidt et al. - 2019 - Challenges to QT Interval Variability Analysis in .pdf;C\:\\Users\\martin\\Zotero\\storage\\XJLB482S\\landing-page.html}
}

2014

  • [DOI] M. Baumert, B. Czippelova, A. Ganesan, M. Schmidt, S. Zaunseder, and M. Javorka, "Entropy Analysis of RR and QT Interval Variability during Orthostatic and Mental Stress in Healthy Subjects," Entropy, vol. 16, iss. 12, p. 6384–6393, 2014.
    [Bibtex] 
    @article{baumert_entropy_2014,
title = {Entropy {{Analysis}} of {{RR}} and {{QT Interval Variability}} during {{Orthostatic}} and {{Mental Stress}} in {{Healthy Subjects}}},
author = {Baumert, Mathias and Czippelova, Barbora and Ganesan, Anand and Schmidt, Martin and Zaunseder, Sebastian and Javorka, Michal},
year = {2014},
month = dec,
journal = {Entropy},
volume = {16},
number = {12},
pages = {6384--6393},
doi = {10.3390/e16126384},
urldate = {2017-12-15},
abstract = {Autonomic activity affects beat-to-beat variability of heart rate and QT interval. The aim of this study was to explore whether entropy measures are suitable to detect changes in neural outflow to the heart elicited by two different stress paradigms. We recorded short-term ECG in 11 normal subjects during an experimental protocol that involved head-up tilt and mental arithmetic stress and computed sample entropy, cross-sample entropy and causal interactions based on conditional entropy from RR and QT interval time series. Head-up tilt resulted in a significant reduction in sample entropy of RR intervals and cross-sample entropy, while mental arithmetic stress resulted in a significant reduction in coupling directed from RR to QT. In conclusion, measures of entropy are suitable to detect changes in neural outflow to the heart and decoupling of repolarisation variability from heart rate variability elicited by orthostatic or mental arithmetic stress.},
copyright = {http://creativecommons.org/licenses/by/3.0/},
langid = {english},
keywords = {complexity,heart rate variability,Heart rate variability,QT variability,stress,sympathetic},
file = {C\:\\Users\\martin\\Zotero\\storage\\3VQU5QAF\\Baumert et al. - 2014 - Entropy Analysis of RR and QT Interval Variability.pdf;C\:\\Users\\martin\\Zotero\\storage\\9KAD6PQZ\\Baumert et al. - 2014 - Entropy Analysis of RR and QT Interval Variability.pdf;C\:\\Users\\martin\\Zotero\\storage\\YALNU8E8\\Baumert et al. - 2014 - Entropy Analysis of RR and QT Interval Variability.pdf;C\:\\Users\\martin\\Zotero\\storage\\3Q5RDX8Q\\6384.html;C\:\\Users\\martin\\Zotero\\storage\\8M9XM3C6\\htm.html;C\:\\Users\\martin\\Zotero\\storage\\Y7CJ422F\\htm.html}
}
  • [DOI] M. Schmidt, M. Baumert, H. Malberg, and S. Zaunseder, "QT Interval Extraction by Two-Dimensional Signal Warping," in Biomedical Engineering / Biomedizinische Technik, Hannover, 2014, p. 154–158.
    [Bibtex] 
    @inproceedings{schmidt_qt_2014,
title = {{{QT}} Interval Extraction by Two-Dimensional Signal Warping},
booktitle = {Biomedical {{Engineering}} / {{Biomedizinische Technik}}},
author = {Schmidt, Martin and Baumert, Mathias and Malberg, Hagen and Zaunseder, Sebastian},
year = {2014},
month = oct,
volume = {59},
pages = {154--158},
publisher = {Walter de Gruyter},
address = {Hannover},
doi = {10.1515/bmt-2014-4069},
abstract = {We propose a novel two-dimensional warping technique to match two one-dimensional patterns. Our approach, referred to as two-dimensional signal warping (2DSW), extends the basic ideas of known warping techniques such as dynamic time warping and correlation optimized warping. By employing two-dimensional piecewise stretching 2DSW is able to capture inhomogeneous variations of one-dimensional signals in direction of abscissa and ordinate. In order to prove the applicability of our method we apply 2DSW for tracking changes in beat-to-beat variability in QT intervals (QTV). Using simulated data we demonstrate the robustness of our approach. Analysis of long-term ECG from the DEFINITE trial on circadian rhythms demonstrated the sensitivity of the proposed algorithm to track changes in the QT interval. Using repeated measure ANOVA and Holm--Bonferroni corrected paired Student's t-test for post-hoc analysis we found statistically significant differences in QTV between 1 a.m. to 8 a.m. and 10 a.m. to 11 p.m.},
isbn = {1862-278X}
}
  • [DOI] M. Schmidt, M. Baumert, A. Porta, H. Malberg, and S. Zaunseder, "Two-Dimensional Warping for One-Dimensional Signals–-Conceptual Framework and Application to ECG Processing," IEEE Transactions on Signal Processing, vol. 62, iss. 21, p. 5577–5588, 2014.
    [Bibtex] 
    @article{schmidt_two-dimensional_2014,
title = {Two-{{Dimensional Warping}} for {{One-Dimensional Signals}}---{{Conceptual Framework}} and {{Application}} to {{ECG Processing}}},
author = {Schmidt, M. and Baumert, M. and Porta, A. and Malberg, H. and Zaunseder, S.},
year = {2014},
month = nov,
journal = {IEEE Transactions on Signal Processing},
volume = {62},
number = {21},
pages = {5577--5588},
issn = {1053-587X},
doi = {10.1109/TSP.2014.2354313},
abstract = {We propose a novel method for evaluating the similarity between two 1d patterns. Our method, referred to as two-dimensional signal warping (2DSW), extends the basic ideas of known warping techniques such as dynamic time warping and correlation optimized warping. By employing two-dimensional piecewise stretching 2DSW is able to take into account inhomogeneous variations of shapes. We apply 2DSW to ECG recordings to extract beat-to-beat variability in QT intervals (QTV) that is indicative of ventricular repolarization lability and typically characterised by a low signal-to-noise ratio. Simulation studies show high robustness of our approach in presence of typical ECG artefacts. Comparison of short-term ECG recorded in normal subjects versus patients with myocardial infarction (MI) shows significantly increased QTV in patients (normal subject 2.36 ms {\textpm} 1.05 ms vs. MI patients 5.94 ms {\textpm} 5.23 ms (mean {\textpm} std), ). Evaluation of a standard QT database shows that 2DSW allows highly accurate tracking of QRS-onset and T-end. In conclusion, the two-dimensional warping approach introduced here is able to detect subtle changes in noisy quasi-periodic biomedical signals such as ECG and may have diagnostic potential for measuring repolarization lability in MI patients. In more general terms, the proposed method provides a novel means for morphological characterization of 1d signals.},
keywords = {Correlation,Cost function,Dynamic time warping,ECG,Electrocardiography,Heuristic algorithms,Physiology,QT,QT interval,QT variability,signal processing,Signal processing algorithms,two-dimensional warping,Vectors,warping},
file = {C:\Users\martin\Zotero\storage\BYDNA77L\6891378.html}
}
  • [DOI] S. Zaunseder, M. Schmidt, H. Malberg, and M. Baumert, "Measurement of QT Variability by Two-Dimensional Warping," in 2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO), 2014, p. 163–164.
    [Bibtex] 
    @inproceedings{zaunseder_measurement_2014,
title = {Measurement of {{QT}} Variability by Two-Dimensional Warping},
booktitle = {2014 8th {{Conference}} of the {{European Study Group}} on {{Cardiovascular Oscillations}} ({{ESGCO}})},
author = {Zaunseder, Sebastian and Schmidt, Martin and Malberg, Hagen and Baumert, Mathias},
year = {2014},
month = may,
pages = {163--164},
doi = {10.1109/ESGCO.2014.6847570},
abstract = {This contribution presents a novel warping method, two-dimensional signal warping (2DSW), for tracking beat-to-beat changes in time intervals from electrocardiograms. To evaluate the efficiency of 2DSW to capture subtle changes in the QT interval we apply 2DSW to the Physionet QT database. It is shown that 2DSW allows highly accurate tracking of QRS-onset and T-end, which renders the method useful for future clinical applications, in particular beat-to-beat variability analysis of ECG features.},
keywords = {2DSW,Algorithm design and analysis,bioelectric potentials,Databases,ECG features,electrocardiograms,electrocardiography,Electrocardiography,Europe,high accurate tracking,medical signal processing,Oscillators,physionet QT database,QRS-onset,QT variability measurement,Standards,time intervals,Time measurement,two-dimensional signal warping method,variability analysis},
file = {C:\Users\martin\Zotero\storage\R7N5YCWD\6847570.html}
}

0001/2014-12-03

  • M. Schmidt, M. Baumert, H. Malberg, and S. Zaunseder, "Iterative Anpassung Eines Verzerrungsgitters Mittels Two-Dimensional Signal Warping Zur QT-Intervall-Extraktion," in Reports on Biomedical Engineering, Dresden, 0001/2014-12-03, p. 83–85.
    [Bibtex] 
    @inproceedings{schmidt_iterative_2014,
title = {Iterative {{Anpassung}} Eines {{Verzerrungsgitters}} Mittels Two-Dimensional Signal Warping Zur {{QT-Intervall-Extraktion}}},
booktitle = {Reports on {{Biomedical Engineering}}},
author = {Schmidt, Martin and Baumert, Mathias and Malberg, Hagen and Zaunseder, Sebastian},
year = {0001/2014-12-03},
volume = {2},
pages = {83--85},
publisher = {Steinbeis-Edition},
address = {Dresden},
isbn = {978-3-95663-018-7}
}