Prof. Dr. Björn Eskofier

Machine Learning and Data Analytics Lab Department Artificial Intelligence in Biomedical Engineering (AIBE)

Akute Anpassungen des Gangbildes und Gleichgewichts an ein sensomotorisches Laufbandtraining bei Patienten mit Morbus Parkinson (2015) Klamroth S, Steib S, Gaßner H, Winkler J, Eskofier B, Klucken J, Pfeifer K Book chapter / Article in edited volumes A framework for early event detection for wearable systems (2015) Dorschky E, Schuldhaus D, Koerger H, Eskofier B Conference contribution, Conference Contribution IMU-based Trick Classification in Skateboarding (2015) Groh B, Kautz T, Schuldhaus D, Eskofier B Conference contribution, Conference Contribution Temporal correction of detected R-peaks in ECG signals: A crucial step to improve QRS detection algorithms (2015) Gradl S, Leutheuser H, Elgendi M, Lang N, Eskofier B Conference contribution, Conference Contribution On Sweat Analysis for Quantitative Estimation of Dehydration during Physical Exercise (2015) Ring M, Lohmüller C, Rauh M, Eskofier B Conference contribution ER-Force Extended Team Description Paper for Robocup 2015 (2015) Eischer M, Blank P, Danzer A, Hauck A, Hoffmann M, Reck B, Eskofier B Conference contribution Comparative Study on Classifying Gait With a Single Trunk-Mounted Inertial-Magnetic Measurement Unit (2015) Full K, Leutheuser H, Schlessmann J, Armitage R, Eskofier B Conference contribution Pull Test Estimation in Parkinson's Disease Patients using Wearable Sensor Technology (2015) Pasluosta CF, Barth J, Gaßner H, Klucken J, Eskofier B Conference contribution, Original article Sensor-based stroke detection and stroke type classification in table tennis (2015) Blank P, Hoßbach J, Schuldhaus D, Eskofier B Conference contribution, Conference Contribution Sampling rate impact on energy consumption of biomedical signal processing systems (2015) Tobola A, Streit FJ, Espig C, Korpok O, Leutheuser H, Sauter C, Lang N, et al. Conference contribution, Conference Contribution