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2020 – today
- 2022
[c12]Marcus Vollmer, Jader Alexander Giraldo Guzmán:
Efficiency of Different Heartbeat Detection Methods by Using Alternative Noise Reduction Algorithms. CinC 2022: 1-4- 2021
- [c11]Philipp Sodmann, Marcus Vollmer
, Lars Kaderali:
Segment, Perceive and Classify - Multitask Learning of the Electrocardiogram in a Single Neural Network. CinC 2021: 1-4 - 2020
- [c10]Philipp Sodmann, Marcus Vollmer:
ECG Segmentation Using a Neural Network as the Basis for Detection of Cardiac Pathologies. CinC 2020: 1-4
2010 – 2019
- 2019
- [c9]Ananya Rajagopalan, Marcus Vollmer:
Rapid Detection of Heart Rate Fragmentation and Cardiac Arrhythmias: Cycle-by-Cycle rr Analysis, Supervised Machine Learning Model and Novel Insights. AIME 2019: 371-375 - [c8]Marcus Vollmer:
HRVTool - an Open-Source Matlab Toolbox for Analyzing Heart Rate Variability. CinC 2019: 1-4 - [c7]Marcus Vollmer, Dominic Bläsing, Lars Kaderali:
Alignment of Multi-Sensored Data: Adjustment of Sampling Frequencies and Time Shifts. CinC 2019: 1-4 - [c6]Marcus Vollmer, Christian F. Luz, Philipp Sodmann, Bhanu Sinha, Sven-Olaf Kuhn:
Time-Specific Metalearners for the Early Prediction of Sepsis. CinC 2019: 1-4 - 2017
- [c5]Marcus Vollmer:
Noise Resistance of Several Top-Scored Heart Beat Detectors. CinC 2017 - [c4]Marcus Vollmer:
Arrhythmia Classification in Long-Term Data Using Relative RR Intervals. CinC 2017 - [c3]Marcus Vollmer, Philipp Sodmann, Leonard Caanitz, Neetika Nath, Lars Kaderali:
Can Supervised Learning Be Used to Classify Cardiac Rhythms?. CinC 2017 - 2015
- [c2]Marcus Vollmer:
A Robust, Simple and Reliable Measure of Heart Rate Variability using Relative RR Intervals. CinC 2015: 609-612 - 2014
- [c1]Marcus Vollmer:
Robust Detection of Heart Beats using Dynamic Thresholds and Moving Windows. CinC 2014: 569-572
Coauthor Index
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