Bjoern M. Eskofier

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Jochen KluckenUniversity of Luxembourg, Luxembourg Institute of Health, Centre Hospitalier du LuxembourgVerified email at uni.lu
Heiko GassnerAssistant Professor, University Hospital ErlangenVerified email at uk-erlangen.de
Jens BarthMaD Lab Erlangen-NürnbergVerified email at fau.de
Patrick KuglerResearcher at the Pattern Recognition Lab, University of Erlangen-NurembergVerified email at cs.fau.de
Jürgen WinklerProfessor für Neurologie, Universitätsklinikum ErlangenVerified email at uk-erlangen.de
Cristian PasluostaResearch Group Leader, University of FreiburgVerified email at imtek.uni-freiburg.de
Heike LeutheuserMachine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-AlexanderVerified email at fau.de
Dominik SchuldhausDigital Sports Group, University of Erlangen-Nürnberg (FAU)Verified email at fau.de
Stefan GradlFriedrich-Alexander University Erlangen-Nürnberg (FAU)Verified email at fau.de
Ulf JensenResearcher at the Pattern Recognition Lab, University of ErlangenVerified email at informatik.uni-erlangen.de
Felix KlugeNovartis Institutes for BioMedical Research (NIBR)Verified email at novartis.com
Joachim HorneggerProfessor of Computer Science, Friedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
Julius HanninkFriedrich-Alexander University Erlangen-Nürnberg (FAU)Verified email at fau.de
Thomas KautzMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
Benjamin H. GrohMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de
Franz MarxreiterDr. med.Verified email at uk-erlangen.de
Christine F. MartindalePhD student, Friedrich-Alexander University Erlangen-NürnbergVerified email at fau.de
Johannes SchlachetzkiUCSDVerified email at glasso.me
Matthias RingVerified email at fau.de
Robert RicherMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-NürnbergVerified email at fau.de

Bjoern M. Eskofier

Heisenberg-Professor for Computer Science Friedrich-Alexander-Universität Erlangen-Nürnberg

Verified email at fau.de - Homepage

Machine Learning Artificial Intelligence Wearable Computing Digital Health Biomedical Engineering


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Technology in Parkinson's disease: challenges and opportunities AJ Espay, P Bonato, FB Nahab, W Maetzler, JM Dean, J Klucken, ... Movement Disorders 31 (9), 1272-1282, 2016	434	2016
An emerging era in the management of Parkinson's disease: wearable technologies and the internet of things CF Pasluosta, H Gassner, J Winkler, J Klucken, BM Eskofier IEEE journal of biomedical and health informatics 19 (6), 1873-1881, 2015	259	2015
Inertial sensor-based stride parameter calculation from gait sequences in geriatric patients A Rampp, J Barth, S Schülein, KG Gaßmann, J Klucken, BM Eskofier IEEE transactions on biomedical engineering 62 (4), 1089-1097, 2014	257	2014
Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems M Elgendi, B Eskofier, S Dokos, D Abbott PloS one 9 (1), e84018, 2014	231	2014
Unbiased and mobile gait analysis detects motor impairment in Parkinson's disease J Klucken, J Barth, P Kugler, J Schlachetzki, T Henze, F Marxreiter, Z Kohl, ... PloS one 8 (2), e56956, 2013	223	2013
Wearable sensors objectively measure gait parameters in Parkinson’s disease JCM Schlachetzki, J Barth, F Marxreiter, J Gossler, Z Kohl, S Reinfelder, ... PloS one 12 (10), e0183989, 2017	212	2017
Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices S Gradl, P Kugler, C Lohmüller, B Eskofier 2012 annual international conference of the IEEE engineering in medicine and …, 2012	195	2012
Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-the-art algorithms using a benchmark dataset H Leutheuser, D Schuldhaus, BM Eskofier PloS one 8 (10), e75196, 2013	171	2013
Stride segmentation during free walk movements using multi-dimensional subsequence dynamic time warping on inertial sensor data J Barth, C Oberndorfer, C Pasluosta, S Schülein, H Gassner, S Reinfelder, ... Sensors 15 (3), 6419-6440, 2015	156	2015
Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards CA Da Costa, CF Pasluosta, B Eskofier, DB Da Silva, R da Rosa Righi Artificial intelligence in medicine 89, 61-69, 2018	155	2018
Biometric and mobile gait analysis for early diagnosis and therapy monitoring in Parkinson's disease J Barth, J Klucken, P Kugler, T Kammerer, R Steidl, J Winkler, ... 2011 Annual International Conference of the IEEE Engineering in Medicine and …, 2011	155	2011
Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment BM Eskofier, SI Lee, JF Daneault, FN Golabchi, G Ferreira-Carvalho, ... 2016 38th Annual International Conference of the IEEE Engineering in …, 2016	131	2016
Sensor-based gait parameter extraction with deep convolutional neural networks J Hannink, T Kautz, CF Pasluosta, KG Gaßmann, J Klucken, BM Eskofier IEEE journal of biomedical and health informatics 21 (1), 85-93, 2016	129	2016
Activity recognition in beach volleyball using a deep convolutional neural network T Kautz, BH Groh, J Hannink, U Jensen, H Strubberg, BM Eskofier Data Mining and Knowledge Discovery 31 (6), 1678-1705, 2017	114	2017
Temporal trajectory aware video quality measure M Barkowsky, J Bialkowski, B Eskofier, R Bitto, A Kaup IEEE Journal of Selected Topics in Signal Processing 3 (2), 266-279, 2009	101	2009
Towards mobile gait analysis: concurrent validity and test-retest reliability of an inertial measurement system for the assessment of spatio-temporal gait parameters F Kluge, H Gaßner, J Hannink, C Pasluosta, J Klucken, BM Eskofier Sensors 17 (7), 1522, 2017	100	2017
An overview of smart shoes in the internet of health things: gait and mobility assessment in health promotion and disease monitoring BM Eskofier, SI Lee, M Baron, A Simon, CF Martindale, H Gaßner, ... Applied Sciences 7 (10), 986, 2017	96	2017
Mobile stride length estimation with deep convolutional neural networks J Hannink, T Kautz, CF Pasluosta, J Barth, S Schülein, KG Gaßmann, ... IEEE journal of biomedical and health informatics 22 (2), 354-362, 2017	91	2017
Multimodal assessment of Parkinson's disease: a deep learning approach JC Vásquez-Correa, T Arias-Vergara, JR Orozco-Arroyave, B Eskofier, ... IEEE journal of biomedical and health informatics 23 (4), 1618-1630, 2018	90	2018
Support vector machines for detecting age-related changes in running kinematics RK Fukuchi, BM Eskofier, M Duarte, R Ferber Journal of Biomechanics 44 (3), 540-542, 2011	85	2011

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