Prof. Dr. Björn Eskofier

Scopus Autoren ID: 26428080900



Organisationseinheit


Stiftungs-Juniorprofessur für Sportinformatik (Digital Sports)
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)


Preise / Auszeichnungen


2018 : Best Student Paper Award
2016 : IEEE EMBS Icehouse Challenge
2012 : Dr. Ahmed Elsaify Memorial Runner-Up Paper Award



Projektleitung

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Anwendung von Deep Learning für Signalanalysen
Prof. Dr. Björn Eskofier
(01.07.2018 - 30.06.2021)

Open Badges: Eine Open-Source Plattform zur Analyse von sozialen Interaktionen und Gruppendynamik
Prof. Dr. Björn Eskofier; Prof. Dr. Alex Pentland
(30.05.2018 - 30.11.2018)

VR Amblyopie Trainer
Prof. Dr. Björn Eskofier
(01.04.2018 - 31.12.2019)

HOOP: mHealth tOol for parkinsOn’s disease training and rehabilitation at Patient’s home
Prof. Dr. Björn Eskofier
(01.02.2018 - 31.01.2019)

Ganganalyse bei geriatrischen Patienten mittels mobiler Sensorsysteme und maschinellem Lernen zur Prädiktion des Sturzrisikos
Prof. Dr. Björn Eskofier; Prof. Dr. Jochen Klucken
(15.01.2018 - 15.01.2021)


Mitarbeit in Forschungsprojekten

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Anwendung von Deep Learning für Signalanalysen
Prof. Dr. Björn Eskofier
(01.07.2018 - 30.06.2021)

moveIT: A novel digital health pathway enables healthcare technologies for gait&falls in Parkinson’s disease
Prof. Dr. Jochen Klucken
(01.01.2018 - 31.12.2018)

BayMed-mGL: Mobile GaITLab: Algorithmik für den Einsatz im Patientenalltag
Prof. Dr. Björn Eskofier; Prof. Dr. Jochen Klucken
(01.08.2017 - 31.01.2019)

C4H - Gesamt: Capital4Health - „Handlungsmöglichkeiten für einen aktiven Lebensstil: ein Forschungsnetzwerk für interaktiven Wissensaustausch in der Gesundheitsförderung“
Prof. Dr. Alfred Rütten
(01.02.2015 - 31.01.2018)

ESI 2: ESI-Anwendungszentrum für die digitale Automatisierung, den digitalen Sport und die Automobilsensorik der Zukunft
Prof. Dr.-Ing. Jürgen Teich
(01.01.2015 - 31.12.2018)


Weitere Forschungsaktivitäten


Vortragstätigkeit
Prof. Dr. Björn Eskofier; Stefan Gradl
Wearable Computing Systems and Machine Learning for Sports Science Research


Publikationen (Download BibTeX)

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Wirth, M., Gradl, S., Poimann, D., Schaefke, H., Matlok, S., Koerger, H., & Eskofier, B. (2018). Assessment of Perceptual-Cognitive Abilities among Athletes in Virtual Environments: Exploring Interaction Concepts for Soccer Players. In ACM New York, NY, USA ©2018 (Eds.), Proceedings of the 2018 Designing Interactive Systems Conference (pp. 1013-1024). Hong Kong, HK: New York.
Moceri, S., Canneva, F., Habermeyer, J., Dobner, J., Schulze-Krebs, A., Puchades, M.,... von Hörsten, S. (2018, March). Association of early phenotypic behavioral alterations in human alpha-synuclein overexpressing transgenic rats with alpha-synuclein/huntingtin/amyloid-beta protein cross-seeding. Poster presentation at Advances in Alzheimer's and Parkinson's Therapies an AAT-AD/PD Focus Meeting, Torino, IT.
Stoffel Antunes, R., Adams Seewald, L., Facco Rodrigues, V., Andre da Costa, C., da Silveira Junior, L.G., da Rosa Righi, R.,... Campanatti, G. (2018). A Survey of Sensors in Healthcare Workflow Monitoring. ACM Computing Surveys, 51(2). https://dx.doi.org/10.1145/3177852
Maurer, M., Kautz, T., Schlenzig, A., Hiemann, A., Zrenner, M., & Eskofier, B. (2018, September). Classification of Match Phases in Handball. Poster presentation at 12. Symposium der Sektion Sportinformatik und Sporttechnologie der Deutschen Vereinigung für Sportwissenschaft (dvs), München, DE.
Zrenner, M., Gradl, S., Jensen, U., Ullrich, M., & Eskofier, B. (2018). Comparison of Different Algorithms for Calculating Velocity and Stride Length in Running Using Inertial Measurement Units. Sensors, 18(12). https://dx.doi.org/10.3390/s18124194
Schellenberger, S., Shi, K., Mai, M., Wiedemann, J.P., Steigleder, T., Eskofier, B.,... Kölpin, A. (2018). Detecting Respiratory Effort-Related Arousals in Polysomnographic Data Using LSTM Networks. (Unpublished, Accepted).
Timotius, I., Canneva, F., Minakaki, G., Pasluosta, C.F., Moceri, S., Casadei, N.,... Eskofier, B. (2018). Dynamic footprint based locomotion sway assessment in α-synucleinopathic mice using Fast Fourier Transform and Low Pass Filter. Journal of Neuroscience Methods, 296, 1-11. https://dx.doi.org/10.1016/j.jneumeth.2017.12.004
Timotius, I., Canneva, F., Minakaki, G., Pasluosta, C.F., Moceri, S., Casadei, N.,... Eskofier, B. (2018). Dynamic footprints of α-synucleinopathic mice recorded by CatWalk gait analysis. Data in Brief, 17, 189-193. https://dx.doi.org/10.1016/j.dib.2017.12.067
Ivanovic, M., Ring, M., Baronio, F., Calza, S., Vukcevic, V., Hadzievski, L.,... Eskofier, B. (2018). ECG derived feature combination versus single feature in predicting defibrillation success in out-of-hospital cardiac arrested patients. Biomedical Physics and Engineering Express, 5(1), 015012. https://dx.doi.org/10.1088/2057-1976/aaebec
Ullrich, M., Gladow, T., Roth, N., Küderle, A., Ollenschläger, M., Gaßner, H.,... Eskofier, B. (2018, July). FallRiskPD: Long-term fall risk classification for Parkinson’s disease via intelligent sensor-based gait analysis in the home environment (Talk). Paper presentation at European Falls Festival 2018, Manchester, GB.

Zuletzt aktualisiert 2016-01-06 um 16:36