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Bjoern M. Eskofier
Researcher at University of Erlangen-Nuremberg
Publications - 314
Citations - 5948
Bjoern M. Eskofier is an academic researcher from University of Erlangen-Nuremberg. The author has contributed to research in topics: Computer science & Gait analysis. The author has an hindex of 32, co-authored 257 publications receiving 4131 citations. Previous affiliations of Bjoern M. Eskofier include Adidas & University of Calgary.
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Journal ArticleDOI
Technology in Parkinson's disease: Challenges and opportunities.
Alberto J. Espay,Paolo Bonato,Fatta B. Nahab,Walter Maetzler,John Dean,Jochen Klucken,Bjoern M. Eskofier,Aristide Merola,Fay B. Horak,Anthony E. Lang,Ralf Reilmann,Joseph P. Giuffrida,Alice Nieuwboer,Malcolm K. Horne,Max A. Little,Irene Litvan,Tanya Simuni,E. Ray Dorsey,Michelle A. Burack,Ken Kubota,Anita Kamondi,Catarina Godinho,Jean-Francois Daneault,Georgia Mitsi,Lothar Krinke,J.M. Hausdorff,Bastiaan R. Bloem,Spyros Papapetropoulos +27 more
TL;DR: The work carried out by the task force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and the quality of life of individuals with PD is summarized.
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An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things
TL;DR: The existing wearable technologies and the Internet-of-Things concept applied to PD are reviewed and discussed, with an emphasis on how this technological platform may lead to a shift in paradigm in terms of diagnostics and treatment.
Journal ArticleDOI
Wearable sensors objectively measure gait parameters in Parkinson's disease.
Johannes C. M. Schlachetzki,Jens Barth,Franz Marxreiter,Julia Gossler,Zacharias Kohl,Samuel Reinfelder,Heiko Gassner,Kamiar Aminian,Bjoern M. Eskofier,J. Winkler,Jochen Klucken +10 more
TL;DR: Wearable sensor-based gait analysis reaches clinical applicability providing a high biomechanical resolution for gait impairment in Parkinson’s disease, and cross-sectional analysis revealed that gait parameters were sensitive to changes by mirroring the progressive nature of Parkinson's disease and corresponded to physician ratings.
Journal ArticleDOI
Unbiased and Mobile Gait Analysis Detects Motor Impairment in Parkinson's Disease
Jochen Klucken,Jens Barth,Patrick Kugler,Johannes C. M. Schlachetzki,Thore Henze,Franz Marxreiter,Zacharias Kohl,Ralph Steidl,Joachim Hornegger,Bjoern M. Eskofier,J. Winkler +10 more
TL;DR: In this article, a mobile, biosensor based Embedded Gait Analysis using Intelligent Technology (eGaIT) consist of accelerometers and gyroscopes attached to shoes that record motion signals during standardized gait and leg function.
Posted Content
Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems
TL;DR: In this paper, the authors investigate current QRS detection algorithms based on three assessment criteria: robustness to noise, parameter choice, and numerical eciency, in order to target a universal fast-robust detector.