Martin Ullrich

Martin Ullrich, M. Sc.

Researcher & PhD Candidate

Department Artificial Intelligence in Biomedical Engineering (AIBE)
Lehrstuhl für Maschinelles Lernen und Datenanalytik

Room 01.026
Carl-Thiersch-Straße 2b
91052 Erlangen

Phone number: +49 9131 85-20159
Email: martin.ullrich@fau.de
Website: https://www.mad.tf.fau.de/person/martin-ullrich/

Research Focus

In many neurological disorders patients are suffering from impaired gait and mobility. Current clinical routine visits can usually not reflect the daily life health status of patients. For more objective observations we attach inertial measurement units (IMUs) to the patients’ shoes or lower back and obtain motion measurements over several days and weeks. My tasks relate to the analysis of the sensor raw data and the extraction of useful clinical information by developing algorithms and software. These can range from the counting of steps per day up to the estimation and prediction of fall risk. The ultimate goal of my research is to make the job of doctors easier and support patients with their disease.

Algorithms for long-term, real-life gait analysis, especially of patients with Parkinson’s disease
Machine-learning based estimation and prediction of fall risk

Academic CV

Since 01/2018	Researcher and Ph.D. student Machine Learning and Data Analytics Lab Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuernberg (FAU)
04/2017 – 09/2017	Visiting Student Human Performance Laboratory (HPL), University of Calgary Research internship with Master Thesis project, Supervisors: Benno Nigg, Vinzenz von Tscharner
10/2015 – 12/2017	Master’s Degree in Medical Engineering Friedrich-Alexander-University Erlangen-Nuernberg (FAU) Master Thesis: Coherence and Pattern Analysis of Bipolar EMG-Currents during Running
10/2011 – 09/2015	Bachelor’s Degree in Medical Engineering Friedrich-Alexander-University Erlangen-Nuernberg (FAU) Bachelor Thesis: “Recognition of Human Gait Using a Single Inertial- Magnetic Measurement Unit and Gait Specific Motion Models” Industrial internships at Dräger Medical GmbH in Lübeck and portabiles GmbH in Erlangen in cooperation with adidas AG in Herzogenaurach

Research Projects

Publications

2022

Roth N., Ullrich M., Küderle A., Gladow T., Marxreiter F., Gaßner H., Kluge F., Klucken J., Eskofier B.:
Real-World Stair Ambulation Characteristics Differ Between Prospective Fallers and Non-Fallers in Parkinson’s Disease
In: IEEE Journal of Biomedical and Health Informatics (2022), p. 1-9
ISSN: 2168-2194
DOI: 10.1109/JBHI.2022.3186766
BibTeX: Download
Ullrich M., Roth N., Küderle A., Richer R., Gladow T., Gaßner H., Marxreiter F., Klucken J., Eskofier B., Kluge F.:
Fall Risk Prediction in Parkinson’s Disease Using Real-World Inertial Sensor Gait Data
In: IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022)
ISSN: 1534-4320
URL: https://ieeexplore.ieee.org/document/9924545
BibTeX: Download

2021

Kluge F., Del Din S., Cereatti A., Gaßner H., Hansen C., Helbostad JL., Klucken J., Küderle A., Mueller A., Rochester L., Ullrich M., Eskofier B., Mazza C.:
Consensus based framework for digital mobility monitoring
In: PLoS ONE 16 (2021)
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0256541
BibTeX: Download
Mazza C., Alcock L., Aminian K., Becker C., Bertuletti S., Bonci T., Brown P., Brozgol M., Buckley E., Carsin AE., Caruso M., Caulfield B., Cereatti A., Chiari L., Chynkiamis N., Ciravegna F., Del Din S., Eskofier B., Evers J., Aymerich JG., Gazit E., Hansen C., Hausdorff JM., Helbostad JL., Hiden H., Hume E., Paraschiv-Ionescu A., Ireson N., Keogh A., Kirk C., Kluge F., Koch S., Küderle A., Lanfranchi V., Maetzler W., Mico-Amigo ME., Mueller A., Neatrour I., Niessen M., Palmerini L., Pluimgraaff L., Reggi L., Salis F., Schwickert L., Scott K., Sharrack B., Sillen H., Singleton D., Soltani A., Taraldsen K., Ullrich M., Van Gelder L., Vereijken B., Vogiatzis I., Warmerdam E., Yarnall A., Rochester L.:
Technical validation of real-world monitoring of gait: a multicentric observational study
In: BMJ Open 11 (2021)
ISSN: 2044-6055
DOI: 10.1136/bmjopen-2021-050785
BibTeX: Download
Richer R., Küderle A., Ullrich M., Rohleder N., Eskofier B.:
BioPsyKit: A Python package for the analysis of biopsychological data
In: Journal of Open Source Software 6 (2021), p. 3702
ISSN: 2475-9066
DOI: 10.21105/joss.03702
URL: https://www.theoj.org/joss-papers/joss.03702/10.21105.joss.03702.pdf
BibTeX: Download
Roth N., Küderle A., Ullrich M., Gladow T., Marxreiter F., Klucken J., Eskofier B., Kluge F.:
Hidden Markov Model based stride segmentation on unsupervised free-living gait data in Parkinson’s disease patients
In: Journal of neuroEngineering and rehabilitation 18 (2021), Article No.: 93
ISSN: 1743-0003
DOI: 10.1186/s12984-021-00883-7
BibTeX: Download
Roth N., Wieland GP., Küderle A., Ullrich M., Gladow T., Marxreiter F., Klucken J., Eskofier B., Kluge F.:
Do We Walk Differently at Home? A Context-Aware Gait Analysis System in Continuous Real-World Environments
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (, 1. November 2021 - 5. November 2021)
DOI: 10.1109/EMBC46164.2021.9630378
BibTeX: Download
Ullrich M., Küderle A., Reggi L., Cereatti A., Eskofier B., Kluge F.:
Machine learning-based distinction of left and right foot contacts in lower back inertial sensor gait data
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (, 1. November 2021 - 5. November 2021)
DOI: 10.1109/EMBC46164.2021.9630653
BibTeX: Download
Ullrich M., Mücke A., Küderle A., Roth N., Gladow T., Gaßner H., Marxreiter F., Klucken J., Eskofier B., Kluge F.:
Detection of unsupervised standardized gait tests from real-world inertial sensor data in Parkinson’s disease
In: IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021), p. 2103-2111
ISSN: 1534-4320
DOI: 10.1109/TNSRE.2021.3119390
URL: https://ieeexplore.ieee.org/abstract/document/9567680
BibTeX: Download

Copyrights

Note for article: “Detection of gait from continuous inertial sensor data using harmonic frequencies”:

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Awards

01/2012 – 12/2017: Scholarship from German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes)
Fritz und Maria Hofmann-Preis (Technische Fakultät, Friedrich-Alexander-Universität Erlangen-Nürnberg) – 2019

Teaching

Innovationlab for Wearable und Ubiquitous Computing

Supervised Projects:

Term	Title
Summer Term 2021	Dungineers
Winter Term 2020 / 21	Argus
Winter Term 2019 / 20	RheumASim
Summer Term 2019	Pen Mates
Winter Term 2018 / 19	Watchstock
Summer Term 2018	Smart Foosball Table

Student Theses

Year	Name	Title
2020	Annika Mücke	Detection of semi-standardized gait tests from free-living inertial sensor recordings in Parkinson’s disease (Bachelor’s Thesis)
2019	Lea Henrich	Evaluation of IMU Orientation Estimation Algorithms Using a Three-Axis Gimbal (Bachelor’s Thesis)
2019	Stefan Fischer	Macro Analysis of free-living Gait in Parkinson’s Disease (Bachelor’s Thesis)
2019	Kevin Rätsch	Clustering of physical activity patterns in COPD patients (Bachelor’s Thesis)

Martin Ullrich

Martin Ullrich, M. Sc.

Research Focus

Academic CV Academic CV

Research Projects Research Projects

Publications Publications

2022

2021

2020

2019

2018

Copyrights Copyrights

Awards Awards

Teaching Teaching

Student Theses Student Theses