Follow
Martin Ullrich
Martin Ullrich
Machine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen
Verified email at fau.de - Homepage
Title
Cited by
Cited by
Year
Technical validation of real-world monitoring of gait: a multicentric observational study
C Mazzà, L Alcock, K Aminian, C Becker, S Bertuletti, T Bonci, P Brown, ...
BMJ open 11 (12), e050785, 2021
632021
Comparison of different algorithms for calculating velocity and stride length in running using inertial measurement units
M Zrenner, S Gradl, U Jensen, M Ullrich, BM Eskofier
Sensors 18 (12), 4194, 2018
552018
Consensus based framework for digital mobility monitoring
F Kluge, S Del Din, A Cereatti, H Gaßner, C Hansen, JL Helbostad, ...
PLoS One 16 (8), e0256541, 2021
392021
Detection of gait from continuous inertial sensor data using harmonic frequencies
M Ullrich, A Kuederle, J Hannink, S Del Din, H Gassner, F Marxreiter, ...
IEEE Journal of Biomedical and Health Informatics, 2020
392020
Hidden Markov Model based stride segmentation on unsupervised free-living gait data in Parkinson’s disease patients
N Roth, A Küderle, M Ullrich, T Gladow, F Marxreiter, J Klucken, ...
Journal of neuroengineering and rehabilitation 18 (1), 93, 2021
312021
Detection of unsupervised standardized gait tests from real-world inertial sensor data in Parkinson’s disease
M Ullrich, A Mücke, A Küderle, N Roth, T Gladow, H Gaßner, F Marxreiter, ...
IEEE Transactions on Neural Systems and Rehabilitation Engineering 29, 2103-2111, 2021
292021
Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium
ME Micó-Amigo, T Bonci, A Paraschiv-Ionescu, M Ullrich, C Kirk, A Soltani, ...
Journal of neuroengineering and rehabilitation 20 (1), 78, 2023
272023
A wavelet based time frequency analysis of electromyograms to group steps of runners into clusters that contain similar muscle activation patterns
V von Tscharner, M Ullrich, M Mohr, D Comaduran Marquez, BM Nigg
PLoS One 13 (4), e0195125, 2018
272018
Fall risk prediction in Parkinson's disease using real-world inertial sensor gait data
M Ullrich, N Roth, A Küderle, R Richer, T Gladow, H Gaßner, F Marxreiter, ...
IEEE journal of biomedical and health informatics 27 (1), 319-328, 2022
212022
Beta, gamma band, and high-frequency coherence of EMGs of vasti muscles caused by clustering of motor units
V von Tscharner, M Ullrich, M Mohr, D Comaduran Marquez, BM Nigg
Experimental brain research 236 (11), 3065-3075, 2018
202018
BioPsyKit: A Python package for the analysis of biopsychological data
R Richer, A Küderle, M Ullrich, N Rohleder, BM Eskofier
Journal of Open Source Software 6 (66), 3702, 2021
172021
Machine learning-based distinction of left and right foot contacts in lower back inertial sensor gait data
M Ullrich, A Küderle, L Reggi, A Cereatti, BM Eskofier, F Kluge
2021 43rd Annual International Conference of the IEEE Engineering in …, 2021
142021
Do we walk differently at home? A context-aware gait analysis system in continuous real-world environments
N Roth, GP Wieland, A Küderle, M Ullrich, T Gladow, F Marxreiter, ...
2021 43rd Annual International Conference of the IEEE Engineering in …, 2021
142021
Mobility recorded by wearable devices and gold standards: the Mobilise-D procedure for data standardization
L Palmerini, L Reggi, T Bonci, S Del Din, ME Micó-Amigo, F Salis, ...
Scientific Data 10 (1), 38, 2023
132023
Robust step detection from different waist-worn sensor positions: implications for clinical studies
M Tietsch, A Muaremi, I Clay, F Kluge, H Hoefling, M Ullrich, A Küderle, ...
Digital biomarkers 4 (Suppl. 1), 50-58, 2020
122020
Kinematic parameter evaluation for the purpose of a wearable running shoe recommendation
M Zrenner, M Ullrich, P Zobel, U Jensen, F Laser, BH Groh, B Duemler, ...
2018 IEEE 15th international conference on wearable and implantable body …, 2018
102018
Design and validation of a multi-task, multi-context protocol for real-world gait simulation
K Scott, T Bonci, F Salis, L Alcock, E Buckley, E Gazit, C Hansen, ...
Journal of NeuroEngineering and Rehabilitation 19 (1), 141, 2022
92022
Unsupervised harmonic frequency-based gait sequence detection for Parkinson's disease
M Ullrich, J Hannink, H Gaßner, J Klucken, BM Eskofier, F Kluge
2019 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2019
82019
Real-world stair ambulation characteristics differ between prospective fallers and non-fallers in Parkinson’s disease
N Roth, M Ullrich, A Küderle, T Gladow, F Marxreiter, H Gassner, F Kluge, ...
IEEE journal of biomedical and health informatics 26 (9), 4733-4742, 2022
62022
Assessing real-world gait with digital technology
ME Micó-Amigo, T Bonci, A Paraschiv-Ionescu, M Ullrich, C Kirk, A Soltani
Validation, insights and recommendations from the Mobilise-D consortium, 2022
52022
The system can't perform the operation now. Try again later.
Articles 1–20