Fall Risk Prediction in Parkinson’s Disease Using Real-World Inertial Sensor Gait Data

Ullrich M, Roth N, Küderle A, Richer R, Gladow T, Gaßner H, Marxreiter F, Klucken J, Eskofier B, Kluge F (2022)

Publication Language: English

Publication Type: Journal article

Publication year: 2022

Journal

IEEE Transactions on Neural Systems and Rehabilitation Engineering Institute of Electrical and Electronics Engineers (IEEE)

URI: https://ieeexplore.ieee.org/document/9924545

DOI: 10.1109/jbhi.2022.3215921

Open Access Link: https://ieeexplore.ieee.org/document/9924545

Authors with CRIS profile

Martin Ullrich Machine Learning and Data Analytics Lab Nils Roth Machine Learning and Data Analytics Lab Arne Küderle Machine Learning and Data Analytics Lab Robert Richer Sonderforschungsbereich 1483/1 Empathokinästhetische Sensorik – Sensortechniken und Datenanalyseverfahren zur empathokinästhetischen Modellbildung und Zustandsbestimmung Heiko Gaßner Department of Molecular Neurology Franz Marxreiter Department of Molecular Neurology Björn Eskofier Machine Learning and Data Analytics Lab Felix Kluge Machine Learning and Data Analytics Lab

Related research project(s)

Empatho-Kinaesthetic Sensor Technology (SFB 1483 EmpkinS) July 1, 2021 - June 30, 2025

Involved external institutions

University of Luxembourg LU Luxembourg (LU) Medical Valley - Europäische Metropolregion Nürnberg DE Germany (DE)

How to cite

APA:

Ullrich, M., Roth, N., Küderle, A., Richer, R., Gladow, T., Gaßner, H.,... Kluge, F. (2022). Fall Risk Prediction in Parkinson’s Disease Using Real-World Inertial Sensor Gait Data. IEEE Transactions on Neural Systems and Rehabilitation Engineering. https://dx.doi.org/10.1109/jbhi.2022.3215921

MLA:

Ullrich, Martin, et al. "Fall Risk Prediction in Parkinson’s Disease Using Real-World Inertial Sensor Gait Data." IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022).

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