Program at a glance
  • Pre-conference Workshop BmSHE: 28.02.2024 11:30-13:00
  • Conference Opening: 28.02.2024 13:00
  • Fachausschusstreffen: 28.02.2024 18:00
  • Social Event: Visit of DPZ 29.02.2024 11:30
  • Conference Dinner: 29.02.2024 19:00
  • Conference Ending: 01.03.2024 14:15
  • Optional Workshops: 01.03.2024 14:30-17:00
  • Optional Social Event: 01.03.2024 17:00
Joana Warnecke

Joana M. Warnecke is a research associate at the University of Cambridge, UK and the Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Germany. She received her M.Sc. in Information Systems from the TU Braunschweig and is currently also a member of the executive committee of the Peter L. Reichertz Institute.

Her current research focuses on the health monitoring of babies in intensive care, developing algorithms for heart and breathing rate as well as the evaluation of video-based systems. As a PhD student she is also designing such sensor systems including machine learning approaches for multimodal sensor fusion for in-vehicle health monitoring.

Joana Warnecke on ResearchGate

Péter Kovács

Péter Kovács completed his habilitation in computer science in 2022; since then, he has been an associate professor at the Department of Numerical Analysis of Eötvös Loránd University in Budapest, Hungary. In 2012, he was a visiting researcher at the Department of Signal Processing, Tampere University of Technology in Finland. From 2018 to 2020, he was a postdoc at the Institute of Signal Processing, Johannes Kepler University Linz in Austria. In 2016, he was honored with the Farkas Gyula Prize in applied mathematics from the János Bolyai Mathematical Society. With over 40 published scientific papers, his work on Variable Projection Networks was recognized with the Hojjat Adeli Award by the International Journal of Neural Systems. He is a member of the public body of the Hungarian Academy of Sciences and the IEEE EMBS Young Professionals Committee.

His main research interests include signal and image processing, numerical analysis, system identification, and explainable AI. Currently, he is focusing on model-driven machine learning, which combines the advantages of traditional model-based signal processing algorithms with the data-driven discipline of deep learning.

Péter Kovács on ResearchGate

Patrique Fiedler studied electrical engineering and information technology at Technische Universität Ilmenau. He received his PhD in biomedical engineering in 2017. Subsequently, he moved to industry from 2017 to 2021 and held various development, project and product management positions at an internationally active medical technology manufacturer. Mr. Fiedler has been a visiting scientist at the University of Porto in Portugal and the University of Pescara-Chieti in Italy on several occasions . Since 2021, Patrique Fiedler returned to academia and currently is Junior Professor and Head of the group "Data Analysis in Life Sciences" at the Institute of Biomedical Engineering and Computer Science at Technische Universität Ilmenau. He also holds an Adjunct Assistant Professor position of the University of Texas Health Center, McGovern Medical School, Department of Pediatrics.

His research interests include data fusion, analysis of multimodal datasets and body sensor networks, as well as the exploration of novel sensor concepts for biomedical applications with a strong focus on neurosciences. Moreover, a focus is the development of online-capable analysis methods for close-to-sensor data processing.

Patrique Fiedler on ResearchGate

Pre-Conference: Networking Meeting BMshE

Last year at the annual DGBMT conference the network BMshE – Women in (bio)medical engineering was founded. We invite all female participants of the workshop to the first follow-up meeting taking place at the conference venue: 28.02.2024, 11:30-13:00. We will meet at the registration desk in lecture hall 24/25 (Med 24/25).

The aim of the meeting is to exchange information and network, the discussion of wishes for the network and the start of planning a of a follow-up event as part of the annual conference of the DGBMT in September in Stuttgart.

Social Event: Visit of DPZ
Foto: Anton Saeckl © Deutsches Primatenzentrum GmbH

On Thursday, 29.02., we are offering you to visit the German Primate Center (DPZ) Göttingen with us, including a guided tour. The research of the DPZ includes basic biological and biomedical questions about the functioning of the body and about evolution and behavior by studying non-human primates. Included are also studies on and the preservation of primate populations in the wild and the improvement of the conditions of animal keeping.

Post-Conference: Workshops

Workshop A: Feature Extraction for Time Series Data with MATLAB

In this hands-on workshop we will discuss common labeling, preprocessing, and feature extraction methods in MATLAB. We will use ECG data as an example, but the methods can be used for various types of timeseries data. We will cover:

  • Preprocessing data to remove outliers and how to deal with missing data.
  • Filtering with the Signal Analyzer App and programmatically.
  • Creating spectrograms and using time-frequency transformations.
  • Automatic Feature Extraction in the time and frequency domain.
  • How to use extracted features for machine learning and deep learning.

Please note: This workshop will not cover the mathematical foundations of these methods. Instead, we will focus on understanding the high-level workings of the methods and how to use them in MATLAB.

Organizational Details:

Franziska Albers

Dr. rer. nat. Franziska Albers is part of the Academia Team at MathWorks and supports researchers in integrating machine learning with MATLAB into their research projects. She studied physics in Heidelberg and Münster and holds a PhD in neuroimaging from University Hospital Münster. Her research background is in multimodal fMRI and MR physics.


Workshop B: How do artificial neural networks really work?

Did you ever wonder what is going on in an artificial neural network on a neural level? Did you ever wonder if we can build a real artificial neural network? In this workshop we will look at a mechanical model of an artificial neural network and understand how the distinct parts like neurons, activation functions, weights etc. function and connect. We will look at logical operators to examine how information flows in a network and how the network learns and adapts to different problems.

No computer programming knowledge is needed.

> Please register here for this workshop <

Axel Schaffland

Axel Schaffland is a PhD student at Osnabrück University working on deep learning concepts and didactics of AI as well as image registration and rephotography. In his project "Mechanical Neural Network" he combines scientific modelling with hand-crafted modelling to make complex connections visible and touchable.


Workshop C: KISSKI - the AI Service centre for sensitive and critical infrastructures

In this session, we will demonstrate hands-on how to use the KISSKI HPC system and provide an overview of our secure HPC service and data management tailored to medical use cases with their special demands on data protection and privacy. We round this quick introduction into our work in KISSKI off with some insights into MLOPs (concepts and best practices for machine learning workflows) and provide you with an overview of our bio-services.

Organizational Details:


> Download program as PDF file <


Wednesday, 28.02.2024
11:30 - 13:00 BMshE Meeting
13:00 - 13:45 Opening Event
13:45 - 14:15 Keynote Patrique Fiedler Sensors and signal processing for mobile out-of-the-lab EEG
14:15 - 15:45 Session: Cardiology I

Sebastian Zaunseder,
Walter Karlen
Joshua Steyer Electrograms in a Cardiac Cell-by-Cell Model
Miriam Cindy Maurer Hunting Bunnies: Comparison of XAI methods for detection of right bundle branch blocks in 12-lead electrocardiograms
Philipp Sodmann Corcodan - A network combining delineation and classification of ECG
Asmus Barth Performance Comparison of Open-Source QRS Detectors Applied to Textile Electrocardiograms
Tabea Steinbrinker Electrocardiography Denoising via Sparse Dictionary Learning from Small Datasets
15:45 - 16:15 Coffee Break
16:15 - 17:45 Session: Neurology I

Patrique Fiedler,
Theresa Bender
Hannes Oppermann Photic driving in single trial EEG in the second harmonics
Paul Anders Simultaneous EEG and OPM-MEG during auditory stimulation
Alina Troglio Automated Spike Sorting in Microneurography: A Proof-of-Concept through Classification on Ground Truth Data
Hiromichi Suetani Exploration of universality and individuality in human EEG: A reservoir computing approach
Magdalena Maurer Comparison of CNN-based EEG classification in sensor and source space
from 18:00 Fachausschusstreffen


Thursday, 29.02.2024
09:00 - 09:30 Keynote
presented by IEEE EMBS
Péter Kovács Interpretable Representation Learning for Biosignals via Variable Projection
09:30 - 11:00 Session: Neurology II

Karin Schiecke,
Johannes Vorwerk
Juan Pablo Fiorenza Testing Predictive Coding through an Information-Theoretic Analysis of Intracranial EEG Recordings
Andreas Erbslöh Phase-dependent Stimulation with Extreme Point Detection of LFP Oscillations in Retinal Recordings
Sven Festag Appreciate the errors! – Can age prediction residua of sleep studies tell us more about patient health?
Andreas Erbslöh Comparison of AI-enhanced Spike Sorting with Digital Autoencoders and Analog Memristors
Tim Erdbrügger Contribution of CutFEM-based MEG source analysis to the reconstruction of the primary somatosensory response: A group study
11:00 - 11:30 Coffee Break
11:30 - 13:00 Social Event Visit of DPZ
13:00 - 13:45 Lunch Break
13:45 - 14:15 Sponsor Session
14:15 - 15:45 Session: Cardiology II

Péter Kovács,
Marcus Vollmer
Jorge Torres Gomez Fine-tuned Circuit Representation of Human Vessels through Reinforcement Learning: A Novel Digital Twin Approach for Hemodynamics
Franz Ehrlich Challenges in the Comparability of Event Detection in Biosignals: A Case Study of Arousal Detection During Sleep
Niels Wessel Magnetocardiography at rest predicts cardiac death in patients with acute chest pain
Tobias Vogelsang Analysis of deep networks for photoplethysmographic blood pressure estimation
Ennio Idrobo-Avila Analysis of electrocardiographic signals to assess heart rate variability under surgical context: a methodological proposal
15:45 - 16:15 Coffee Break
16:15 - 17:45 Poster Session

Andreas Erbslöh,
Ennio Idrobo-Avila
Alparslan Babur Posture estimation by analysing the pressure distribution on a cushion using machine learning
Nico Blass Real-time Neonatal Respiratory Rate Extraction using Deep Learning and Domain Transfer
Gergő Galiger Decision validity of heatmap-based explainable neural networks – an explanation first approach
Lennart Graf Extending the AcuWave Software Suite by a DICOMweb™ Plugin
Oruç Kahriman Optimizing Transformer Architecture for Time Series Analysis in Cardiovascular Signal Processing
Lucas Klauth Conception of an AI-Based Recommender System for Labeling Ballistocardiographic Data
Dominik Kranz Can Diffusion Models Understand the Long Term Dependencies in an ECG?
Marlen Kruse Direction of magnetic field vectors in relation to OPM sensor positions at abductor digiti minimi
Sebastian Schmale EFC: An open-source Python library for electrocardiography format conversion
Charlotte Sielaff Long-Term Quality of Neural Signals: Criteria for Intracortical Implants
Vitali Telezki Deployment of an HPC-Accelerated Research Data Management System: Exemplary Workflow in HeartAndBrain Study
Thorge von der Ohe Detecting pulsatile motion of blood vessels in Real-Time MRI
Tiezhi Wang Assessing the importance of long-range correlations for deep-learning-based sleep staging
Jakob Winkler Physics informed EEG source localization with deep learning
Diana Zahn Cobalt ferrite nanoparticles for magnetic heating
Philip Zaschke Extending a Biosignal Data Managing Platform by High Performance Computing for Reproducible Processing Workflows
from 19:00 Conference Dinner at Myer's


Friday, 01.03.2024
09:00 - 09:30 Keynote
presented by KISSKI
Joana Warnecke Continuous Monitoring Enabled with Multimodal Signal Fusion during Driving
09:30 - 11:00 Session: Novel Methods

Saswati Pal,
Markus Lüken
Rafal Zdunek Linked CP Decomposition Model with Beta-divergence for Multimodal Signal Classification
Laureen Wegert Biophysiological Model of the Phrenic Nerve
Andreas Erbslöh Classification of ON- and OFF-Retinal Ganglion Cell Types in Extracelluar Recordings
Lisa Yvonne Debus Reinforcement Learning-based Receiver for Molecular Communication with Mobility
Saswati Pal Impact of Gateway Placement on Cancer Detection in Blood Vessels
11:00 - 11:30 Sponsor Session
11:30 - 13:00 Session: Imaging

Joana Warnecke,
Thomas Penzel
Idoia Badiola Mapping of peripheral venous hemodynamics using a low-cost camera: a proof-of-concept
Florian Voss Camera Fusion for Improving Body Part Segmentation of Preterm Infants
Carlo Caruso Machine Learning based analysis of transcranial ultrasound for the non-invasive assessment of the intracranial pressure state
Tamás Dózsa Modeling CT images in the presence of beam hardening
13:00 - 13:45 Award Session
13:45 - 14:15 Closing Event
14:30 - 17:00 Workshops