Stiftungs-Juniorprofessur für Sportinformatik (Digital Sports)

Reallocation / Closing: 01/03/2017
Address:
Haberstraße 2
91058 Erlangen


Related Project(s)


(E-Home-Center):
MotionLab@Home: Multimodal movement analysis system for therapy monitoring
Prof. Dr. Björn Eskofier
(01/10/2015 - 31/12/2016)



Publications

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Gaßner, H., Steib, S., Klamroth, S., Pasluosta, C.F., Adler, W., Eskofier, B.,... Klucken, J. (2019). Perturbation Treadmill Training Improves Clinical Characteristics of Gait and Balance in Parkinson's Disease. Journal of Parkinson's Disease, 9(2), 413-426. https://dx.doi.org/10.3233/JPD-181534
Steib, S., Klamroth, S., Gaßner, H., Pasluosta, C.F., Eskofier, B., Winkler, J.,... Pfeifer, K. (2019). Exploring gait adaptations to perturbed and conventional treadmill training in Parkinson’s disease: Time-course, sustainability, and transfer. Human Movement Science. https://dx.doi.org/10.1016/j.humov.2019.01.007
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
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.
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
Hannink, J., Kautz, T., Pasluosta, C.F., Barth, J., Schülein, S., Gassmann, K.-G.,... Eskofier, B. (2018). Mobile Stride Length Estimation with Deep Convolutional Neural Networks. IEEE Journal of Biomedical and Health Informatics, 22(2), 354 - 362. https://dx.doi.org/10.1109/JBHI.2017.2679486
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
Groh, B., Fritz, J., Deininger, M., Schwameder, H., & Eskofier, B. (2018). Unobtrusive and Wearable Landing Momentum Estimation in Ski Jumping with Inertial-Magnetic Sensors. In IEEE (Eds.), Proceedings of the 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN) (pp. 102-105). Las Vegas, USA.
Tobola, A., Leutheuser, H., Pollak, M., Spies, P., Hofmann, C., Weigand, C.,... Fischer, G. (2018). Self-powered Multiparameter Health Sensor. IEEE Journal of Biomedical and Health Informatics, 22(1), 15-22.
Kluge, F., Hannink, J., Pasluosta, C.F., Klucken, J., Gaßner, H., Gelse, K.,... Krinner, S. (2018). Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty. Gait & Posture, 66, 194-200. https://dx.doi.org/10.1016/j.gaitpost.2018.08.026
Vasquez Correa, J., Arias Vergara, T., Rafael Orozco-Arroyave, J., Eskofier, B., Klucken, J., & Nöth, E. (2018). Multimodal assessment of Parkinson's disease: a deep learning approach. IEEE Journal of Biomedical and Health Informatics. https://dx.doi.org/10.1109/JBHI.2018.2866873
Orlemann, T., Zenker, B., Reljic, D., Meyer, J., Meyer, J., Oberlaender, J.,... Zopf, Y. (2018). Recording and Optimizing the Nutritional Behavior of oncological Patients by using a Smartphone App (OncoFood). (pp. S28-S29).
Gradl, S., Cibis, T., Lauber, J., Richer, R., Rybalko, R., Pfeiffer, N.,... Eskofier, B. (2017). Wearable Current-Based ECG Monitoring System with Non-Insulated Electrodes for Underwater Application. Applied Sciences, 7(12). https://dx.doi.org/10.3390/app7121277
Steib, S., Klamroth, S., Gaßner, H., Pasluosta, C.F., Eskofier, B., Winkler, J.,... Pfeifer, K. (2017). Perturbation during treadmill training improves dynamic balance and gait in Parkinson’s disease: A single-blind randomized controlled pilot trial. Neurorehabilitation and Neural Repair, 31(8), 758-768. https://dx.doi.org/10.1177/1545968317721976
Hannink, J., Kautz, T., Pasluosta, C.F., Gaßmann, K.-G., Klucken, J., & Eskofier, B. (2017). Sensor-based Gait Parameter Extraction with Deep Convolutional Neural Networks. IEEE Journal of Biomedical and Health Informatics, 21(1), 85--93. https://dx.doi.org/10.1109/JBHI.2016.2636456
Knorz, S., Kluge, F., Gelse, K., Schulz-Drost, S., Hotfiel, T., Lochmann, M.,... Krinner, S. (2017). Three-Dimensional Biomechanical Analysis of Rearfoot and Forefoot Running. Orthopaedic Journal of Sports Medicine, 5(7). https://dx.doi.org/10.1177/2325967117719065
Christian, J., Kluge, F., Eskofier, B., & Schwameder, H. (2017). Comparison of different marker sets for marker trajectory and principal component analysis based classification of simulated gait impairments. Journal of Biomedical Engineering and Informatics, 3(1), 10-17. https://dx.doi.org/10.5430/jbei.v3n1p10
Leutheuser, H., Lang, N., Gradl-Trautvetter, S., Struck, M., Tobola, A., Hofmann, C.,... Eskofier, B. (2017). Textile Integrated Wearable Technologies for Sports and Medical Applications. In Stefan Schneegass, Oliver Amft (Eds.), Smart Textiles. (pp. 359-382).
Kautz, T., Groh, B., Hannink, J., Jensen, U., Strubberg, H., & Eskofier, B. (2017). Activity recognition in beach volleyball using a Deep Convolutional Neural Network. Data Mining and Knowledge Discovery, 31(6), 1678–1705. https://dx.doi.org/10.1007/s10618-017-0495-0
Groh, B., Fleckenstein, M., Kautz, T., & Eskofier, B. (2017). Classification and visualization of skateboard tricks using wearable sensors. Pervasive and Mobile Computing, 40, 42-55. https://dx.doi.org/10.1016/j.pmcj.2017.05.007


Publications in addition


Duits, R., Janssen, M.H.J., Hannink, J., & Sanguinetti, G.R. (2016). Locally Adaptive Frames in the Roto-Translation Group and Their Applications in Medical Imaging. Journal of Mathematical Imaging and Vision, 1-36. https://dx.doi.org/10.1007/s10851-016-0641-0

Last updated on 2019-24-04 at 18:28