Homepage of Marcus Vollmer

Marcus Vollmer

Listen to the DGBMT podcast "Signals for Life"

Ongoing Research Projects (at the time of 2019, update follows)

Clinical sepsis research | SepsisDialog

Our research is focussed on the new sepsis definition, medication during the acute phase of severe sepsis and septic show and on computer assisted sepsis diagnostics.

Sreening for Leiomyosarcoma | DKSM

About 50% of all leiomyosarcoma were treated according to the leiomyoma treatment protocol, because malignancy was not suspected at the time of surgery. We are working on a screening system to reduce the number of inadequate surgery using data from the DKSM (German Clinical Center of Excellence for Genital Sarcomas and Mixed Tumors) and outpatient study center.

Cardiovascular diseases | DZHK

We are currently screening and evaluating data of the orthostatic test from the cross-sectional study SHiP (Study of Health in Pomerania). In particular we are looking for clinical marker of the coronary artery disease.

Smell Capacity Disorders

In cooperation with Dr. Beule (ENT) we are working on the prevalence and aetiology of smell capacity disorders. We use data from the SHiP study.

Endoscopic Third Ventriculostomy

In cooperation with Dr. Marx (Neurosurgery) we are working on a score system for predicting the success of the ETV which incorporates liquor data.

Heart Rate Variability and Annotation/Segmentation of the ECG

  • Robust Detection of Heart Beats in Multimodal Data: the PhysioNet/Computing in Cardiology Challenge 2014 (see challenge); UPDATE: 1st place in Phase I, Phase II: 2nd, Phase III: 5th. Abstract, QRS Detection (Comic).
  • Measures of Heart Rate Variability / Use of relative RR Intervals (see
  • AF Classification from a short single lead ECG recording: the PhysioNet/Computing in Cardiology Challenge 2017 (see challenge);
  • ECG Working Group


Pötter LA, Vollmer M, Santamaria RM, Splieth CH, Schmoeckel J (2024)
Performance of restorations in primary molars over a seven-year period
Journal of Dentistry, 2024; 105121; DOI:10.1016/j.jdent.2024.105121

Gebhardt S, Vollmer M, Zimmerer A, Rochel I, Balcarek P, Niemeyer P, Wassilew GI (2024)
Factors affecting choice of surgical treatment of cartilage lesions of the knee - an analysis of data from 5143 patients from the German Cartilage Registry (Knorpelregister DGOU)
The Orthopaedic Journal of Sports Medicine, 2024; accepted for publication; DOI:

Fuchs C, Scheer CS, Wauschkuhn S, Vollmer M, Meissner K, Hahnenkamp K, Gründling M, Selleng S, Thiele T, Borgstedt R, Kuhn S-O, Rehberg S, Scholz SS (2024)
Continuation of chronic antiplatelet therapy is not associated with increased need for transfusions: a cohort study in critically ill septic patients
BMC Anesthesiology, 2024; 24(1):146; DOI:10.1186/s12871-024-02516-7

Gil O, Fenske B, Bremert T, Vollmer M, Scharf C, Busch C-J, Blaurock M (2024)
Prevalence of Obstructive Sleep Apnea in Head and Neck Squamous Cell Carcinoma Patients before and after Treatment
Medicina, 2024; 60(2), 310; DOI:10.3390/medicina60020310

Gründling M, Scheer CS, Vollmer M (2024)
Remote Patient Monitoring bei SARS-COV-II-Infektionen - zentrale Aspekte und Erkenntnisse zu einem Pilotprojekt
In: McKinsey & Company (Ed.), Pirkka Padmanabhan (Ed.), Matthias Redlich (Ed.), Laura Richter (Ed.), Tobias Silberzahn (Ed.); E-Health Monitor 2023/24: Deutschlands Weg in die digitale Gesundheitsversorgung - Status quo und Perspektiven; Medizinisch Wissenschaftliche Verlagsgesellschaft, Berlin 2024; p195-209; ISBN:978-3-95466-860-1

Bergquist T, Schaffter T, Yan Y, Yu T, Prosser J, Gao J, Chen G, Charzewski Ł, Nawalany Z, Brugere I, Retkute R, Prusokas A, Prusokas A, Choi Y, Lee S, Choe J, Lee I, Kim S, Kang J, Mooney SD, Guinney J, the Patient Mortality Prediction DREAM Challenge Consortium (2024)
Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine
Journal of the American Medical Informatics Association, 2024; 31(1), 35-44; DOI:10.1093/jamia/ocad159

Bremer JP, Neyazi M, Knorr MS, Vollmer M, Groß S, Brederecke J, Ojeda FM, Dörr M, Blankenberg S, Schnabel RB (2023)
Deep learning based prediction of atrial fibrillation incidence from 1-lead ECGs: a model development and validation study
European Heart Journal, 2023; 44, Issue Supplement_2 ehad655.2931; DOI:10.1093/eurheartj/ehad655.2931

Neyazi M, Bremer JP, Knorr MS, Groß S, Brederecke J, Schweingruber N, Csengeri D, Schrage B, Bahls M, Friedrich N, Zeller T, Felix S, Blankenberg S, Dörr M, Vollmer M, Schnabel RB (2023)
Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community
Clinical Chemistry and Laboratory Medicine, 2024; 62(4), 740-752; DOI:10.1515/cclm-2023-0743

Idelevich EA, Nedow B, Vollmer M, Becker K (2023)
Evaluation of a Novel Benchtop Tool for Acceleration of Sample Preparation for MALDI-TOF Mass Spectrometry
Journal of Clinical Microbiology, 2023; 61(8):e00212-23; DOI:10.1128/jcm.00212-23

Krause E, Vollmer M, Wittfeld K, Weihs A, Frenzel S, Dörr M, Kaderali L, Felix SB, Stubbe B, Ewert R, Völzke H, Grabe HJ (2023)
Evaluating heart rate variability with 10-second multichannel electrocardiograms in a large population-based sample
Frontiers in Cardiovascular Medicine, 2023; 10, 598; DOI:10.3389/fcvm.2023.1144191

Konschake W, Riebe H, Vollmer M, Jünger M (2023)
Health-related quality of life during different stages of decongestive therapy on patients with lymphoedema of the legs
Journal of the European Academy of Dermatology & Venereology, 2023; 37:e872–e873; DOI:10.1111/jdv.18968

Vollmer M, Bläsing D, Reiser JE, Nisser M, Buder A (2023)
Simultaneous physiological measurements with five devices at different cognitive and physical loads (version 1.0.2)
PhysioNet, 2020; DOI:10.13026/wce5-fj54

Reichert VM, Alwafai Z, Zygmunt MT, Vollmer M, Köhler G (2023)
Accidental morcellation of uterine leiomyosarcoma influences relapse free survival but Does Not negatively influence overall survival
Journal of Clinical Medicine, 2023; 12(2), 591; DOI:10.3390/jcm12020591

Konschake W, Riebe H, Vollmer M, Jünger M (2022)
Optimisation of intermittent pneumatic compression in patients with lymphoedema of the legs
European Journal of Dermatology, 2022; 32(6), 781-792; DOI:10.1684/ejd.2022.4382

Bläsing D, Buder A, Reiser JE, Nisser M, Derlien S, Vollmer M (2022)
ECG performance in simultaneous recordings of five wearable devices using a new morphological noise-to-signal index and Smith-Waterman-based RR interval comparisons
PloS ONE, 2022; 17(10); e0274994; DOI:10.1371/journal.pone.0274994

Vollmer M, Giraldo Guzmán JA (2022)
Efficiency of different heartbeat detection methods by using alternative noise reduction algorithms
Computing in Cardiology (CinC), 2022; Vol 49; ISSN: 2325-887X; DOI:10.22489/CinC.2022.034

Bogaczyk V, Fleck S, Berneiser J, Opolka M, Vollmer M, Baldauf J, Schroeder H, Marx SJ, Gasch CM, Lemke EM, El Refaee E, Matthes M, Hirschfeld H, Lauffer H, Gaab M (2022)
Long-term quality of life after ETV or ETV with consecutive VP shunt placement in hydrocephalic pediatric patients
Child's Nervous System, 2022; 38(10), 1885-1894; DOI:10.1007/s00381-022-05590-9

Vollmer M, Bläsing D, Reiser JE, Nisser M, Buder A (2022)
Simultaneous physiological measurements with five devices at different cognitive and physical loads (version 1.0.1)
PhysioNet, 2020; DOI:10.13026/zhns-t386

Junge F, Konschake W, Haase H, Vollmer M, Jünger M (2022)
Walking instead of standing: Influence of movement on sensations of discomfort and the volume of the lower legs during standing loads
VASA, 2022; DOI:10.1024/0301-1526/a000990

Al Menabbawy A, El Rafaee E, Elwy R, Salem AA, Lehmann S, Vollmer M, Matthes M, Fleck S, Baldauf J, Schröder H W S (2022)
A multivariable prediction model for recovery patterns and time course of symptoms improvement in hemifacial spasm following microvascular decompression
Acta Neurochirurgica, 164:833-844, 2022; DOI:10.1007/s00701-022-05133-w

Sodmann P F, Kaderali L, Vollmer M (2021)
Segment, Perceive and Classify-Multitask Learning of the Electrocardiogram in a Single Neural Network
Computing in Cardiology (CinC), 2021; Vol 48; ISSN: 2325-887X; DOI:10.22489/CinC.2021.129

Friedrich S, Groß S, König I R, Engelhardt S, Bahls M, Heinz J, Huber C, Kaderali L, Kelm M, Leha A, Rühl J, Schaller J, Scherer C, Vollmer M, Seidler T, Friede T (2021)
Applications of AI/ML approaches in cardiovascular medicine: A systematic review with recommendations
European Heart Journal - Digital Health, 2021; DOI:10.1093/ehjdh/ztab054

Gamain J, Herr T, Fleischmann R, Stenner A, Vollmer M, Willert C, Veit B, Lehnert B, Müller J-U, Steigerwald F, Tost F, Kronenbürger M (2021)
Smell and taste in idiopathic blepharospasm
Journal of Neural Transmission, 2021; DOI:10.1007/s00702-021-02366-4

Metelmann C, Metelmann B, Schuffert L, Hahnenkamp K, Vollmer M, Brinkrolf P (2021)
Smartphone apps to support laypersons in bystander CPR are of ambivalent benefit: a controlled trial using medical simulation
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 29:76, 2021; DOI:10.1186/s13049-021-00893-3

Metelmann B, Brinkrolf P, Kliche M, Vollmer M, Hahnenkamp K, Metelmann C (2021)
Emergency medical service, medical on-call service, or emergency department: Germans unsure whom to contact in acute medical events
Medizinische Klinik, Intensivmedizin und Notfallmedizin, 117, 144-151 2022; DOI:10.1007/s00063-021-00820-5

Ramminger S, Holzapfel C, Marra M, Lamers D, Poggiogalle E, Sealy M, Englert I, Boschmann M, Keil JP, Gärtner S, Vollmer M, Fischer D-C, Valentini L (2020)
Age-related decline of resting energy expenditure in humans with similar body weight: First results of the indirect-calorimetry (IC-) Basarot project
Clinical Nutrition ESPEN, 40, 485-486, 2020; DOI:10.1016/j.clnesp.2020.09.240

Ramminger S, Holzapfel C, Marra M, Lamers D, Poggiogalle E, Sealy M, Englert I, Boschmann M, Keil JP, Gärtner S, Vollmer M, Fischer D-C, Valentini L (2020)
Darstellung des indirekte Kalorimetrie-basierten Ruheenergieumsatzes über Geschlecht, Alter, BMI und Körpergewicht: Erste Ergebnisse einer multizentrischen, internationalen Querschnittsanalyse mit 2187 gesunden Personen
Aktuelle Ernährungsmedizin, 45(03):5, 2020; DOI:10.1055/s-0040-1710210

Herr T, Gamain J, Fleischmann R, Lehnert B, Vollmer M, Willert C, Veit B, Stenner A, Müller J-U, Caspers B, Kronenbürger M (2020)
Olfaction as a Marker for Dystonia: Background, Current State and Directions
Brain Sciences, 10(10), 727, 2020; DOI:10.3390/brainsci10100727

Sodmann P, Vollmer M (2020)
ECG Segmentation Using a Neural Network as the Basis for Detection of Cardiac Pathologies
Computing in Cardiology (CinC), 2020; Vol 47; ISSN: 2325-887X; DOI:10.22489/CinC.2020.356

Vollmer M, Bläsing D, Reiser JE, Nisser M, Buder A (2020)
Simultaneous physiological measurements with five devices at different cognitive and physical loads (version 1.0.0)
PhysioNet, 2020; DOI:10.13026/chd5-t946

El Damaty A, Marx S, Cohrs G, Vollmer M, Eltanahy A, El Refaee E, Baldauf J, Fleck S, Baechli H, Zohdi A, Synowitz M, Unterberg A, Schroeder HWS (2020)
ETV in infancy and childhood below 2 years of age for treatment of hydrocephalus
Child's Nervous System, 2020; DOI:10.1007/s00381-020-04585-8

Luz C, Vollmer M, Decruyenaere J, Nijsten M, Glasner C, Sinha B (2020)
Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies
Clinical Microbiology and Infection, 26(10), 1291-1299; DOI:10.1016/j.cmi.2020.02.003

Herr T, Hummel T, Vollmer M, Willert C, Veit B, Gamain J, Fleischmann R, Lehnert B, Müller J-U, Stenner A, Kronenbürger M (2020)
Smell and taste in cervical dystonia
Journal of Neural Transmission, 127(3), 346-354; DOI:10.1007/s00702-020-02156-4

Schwarzenbacher J, Kuhn S-O, Vollmer M, Scheer C, Fuchs C, Rehberg S, Balau V, Hahnenkamp K, Bohnert J A, Gründling M (2019)
On-site blood culture incubation shortens the time to knowledge of positivity and microbiological results in septic patients
PLoS ONE, 2019; 14(12):e0225999; DOI:10.1371/journal.pone.0225999

Metelmann B, Metelmann C, Schneider L, Vollmer M, Fischer M, Bohn A, Hahnenkamp K, Brinkrolf P (2019)
Anstieg der Laienreanimationsrate in Deutschland geht mit vermehrter Telefonreanimation einher / Increase in bystander-CPR within a decade accompanies rise in telephone-CPR
Der Notarzt, 35(06), 323-328; DOI:10.1055/a-1039-3693

Scheer CS, Kuhn S-O, Vollmer M, Hahnenkamp K, Rehberg S (2019)
Reply to the Letter to the Editor: Earlier Recognition of Sepsis and Septic Shock With Sepsis-3 Criteria - It's Still Early Days!
Shock, Oct 19; DOI:10.1097/SHK.0000000000001461

Vollmer M, Bläsing D, Kaderali L (2019)
Alignment of Multi-Sensored Data: Adjustment of Sampling Frequencies and Time Shifts
Computing in Cardiology (CinC), 2019; Vol 46; ISSN: 2325-887X; DOI:10.22489/CinC.2019.031

Vollmer M, Luz CF, Sodmann P, Sinha B , Kuhn S-O (2019)
Time-specific Metalearners for the Early Prediction of Sepsis
Computing in Cardiology (CinC), 2019; Vol 46; ISSN: 2325-887X; DOI:10.22489/CinC.2019.029

Vollmer M (2019)
HRVTool - an Open-Source Matlab Toolbox for Analyzing Heart Rate Variability
Computing in Cardiology (CinC), 2019; Vol 46; ISSN: 2325-887X; DOI:10.22489/CinC.2019.032

Köhler G, Vollmer M, Nath N, Hessler PA, Dennis K, Lehr A, Köller M, Riechmann C, Bralo H, Trojnarska D, Lehnhoff H, Krichbaum J, Krichbaum M, Evert K, Evert M, Zygmunt MT, Kaderali L (2019)
Benign uterine mass - discrimination from leiomyosarcoma by a preoperative risk score: a multicenter cohort study.
Archives of Gynecology and Obstetrics, 300(6), 1719-1727; DOI:10.1007/s00404-019-05344-0

Westphal T, Konschake W, Haase H, Vollmer M, Jünger M, Riebe H (2019)
Medical compression stockings on the skin moisture in patients with chronic venous disease.
Vasa, Vol 48, 502-508; DOI:10.1024/0301-1526/a000812

Rajagopalan A, Vollmer M (2019)
Rapid Detection of Heart Rate Fragmentation and Cardiac Arrhythmias: Cycle-by-Cycle rr Analysis, Supervised Machine Learning Model and Novel Insights.
In: Riaño D., Wilk S., ten Teije A. (eds) Artificial Intelligence in Medicine. AIME 2019. Lecture Notes in Computer Science, vol 11526. Springer, Cham; DOI:10.1007/978-3-030-21642-9_47

Scheer CS, Fuchs C, Gründling M, Vollmer M, Bast J, Bohnert JA, Zimmermann K, Hahnenkamp K, Rehberg S, Kuhn SO (2019)
Impact of antibiotic administration on blood culture positivity at the beginning of sepsis: a prospective clinical cohort study
Clinical Microbiology and Infection, 25(3), 326-331; DOI:10.1016/j.cmi.2018.05.016

Scheer CS, Kuhn S, Fuchs C, Vollmer M, Modler M, Brunkhorst F, Shankar-Hari M, Hahnenkamp K, Gründling M, Rehberg S. (2018)
Do Sepsis-3 criteria facilitate earlier recognition of sepsis and septic shock? A retrospective cohort study
Shock, 51(3), 306-311; DOI:10.1097/SHK.0000000000001177; Link to PDF

Sodmann P, Vollmer M, Nath N, Kaderali L (2018)
A Convolutional Neural Network for ECG Annotation as the Basis for Classification of Cardiac Rhythms
Physiological Measurement, 2018; 39(10); DOI:10.1088/1361-6579/aae304

Vollmer M, Sodmann P, Caanitz L, Nath N, Kaderali L (2017)
Can Supervised Learning Be Used to Classify Cardiac Rhythms?
Computing in Cardiology (CinC), 2017; Vol 44; ISSN: 2325-887X; DOI:10.22489/CinC.2017.347-176

Vollmer M (2017)
Noise Resistance of Several Top-Scored Heart Beat Detectors
Computing in Cardiology (CinC), 2017; Vol 44; ISSN: 2325-887X; DOI:10.22489/CinC.2017.182-178

Vollmer M (2017)
Arrhythmia Classification in Long-Term Data Using Relative RR Intervals
Computing in Cardiology (CinC), 2017; Vol 44; ISSN: 2325-887X; DOI:10.22489/CinC.2017.213-185

Fuchs C, Wauschkuhn S, Scheer CS, Vollmer M, Meissner K, Kuhn S, Hahnenkamp K, et al. (2017)
Continuing chronic beta-blockade in the acute phase of severe sepsis and septic shock is associated with decreased mortality rates up to 90 days
British Journal of Anaesthesia, 2017; 119(4), p 616-625. DOI:10.1093/bja/aex231

Scheer CS, Fuchs C, Kuhn S, Vollmer M, Rehberg S, Meissner K, et al. (2017)
Quality Improvement Initiative for Severe Sepsis and Septic Shock Reduces 90-Day Mortality: A 7.5-Year Observational Study
Critical Care Medicine, 2017; 45(2), p 241-252. DOI:10.1097/CCM.0000000000002069; Link to PDF

Vollmer M (2015)
A Robust, Simple and Reliable Measure of Heart Rate Variability using Relative RR Intervals
Computing in Cardiology Conference (CinC), 2015; Nice, France; ISSN: 2325-8861; p 609-612.

Vollmer M (2014)
Robust Detection of Heart Beats using Dynamic Thresholds and Moving Windows
Computing in Cardiology Conference (CinC), 2014; Cambridge, MA; ISSN: 2325-8861; p 569-572.

Teaching Experience

Presentations and Posters

What is Heart Rate and How do we Measure Heart Rate Variability?

Young-DZHK CardioLunch (Greifswald 2019)

Estimation of Sample Size and Power for Dunnetts Testing Setups with Unequal Effect Sizes

Adaptive Designs and Mutiple Testing Procedures (Bremen 2018)

Can Supervised Learning be used to Classify Cardiac Rhythms?

Computing in Cardiology (Rennes 2017)

Noise Resistance of Several Top-Scored Heart Beat Detectors

Computing in Cardiology (Rennes 2017)

Randomized Model Selection as a Model Building Strategy in Stepwise Logistic Regression

Potsdam Conference on Structural Inference in Statistics 2013

Die USA haben 25-Cent-Münzen. Warum hat der Euro keine?

Kinder- und Jugenduni Greifswald 2013

A circular distribution family and tests for independence

Copulae in mathematical and quantitative finance (Kraków 2012)

A new Independence Test for continuous variables

Computing & Statistics (ERCIM'11) (London 2011)

GRaP Independence Test

17. DStatG Nachwuchsworkshop (Leipzig 2011)

GRaP Independence Test (Animationen nur im Vollbildmodus)

Weihnachtskolloquium 2010

Software/ Applications/ OpenSource

HRVTool for Matlab
A user friendly application for screening and manipulation of ECG data and the analysis of heart rate variability.
Please visit the project page on GitHub The application is licensed under MIT license.

DataDownload for Matlab
An application to list and download lots of files with specific file extensions from websites and servers.
Matlab Centrals Pick of the week in January 2019.

LiveRecording for Matlab
Recording audio signals from an input device with real-time analysis of the immediate signal showing the spectrogram.
Upon request I provide a standalone executable.


R helper functions
R functions for summary statistics and statistical analysis.


Notebooks introducing specific topics of data analysis with R.