Bjoern M. Eskofier

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Jochen KluckenUniversity of Luxembourg, Centre Hospitalier du LuxembourgVerifierad e-postadress på uni.lu
Heiko GassnerIndependent Group Leader, University Hospital ErlangenVerifierad e-postadress på uk-erlangen.de
Jens BarthMaD Lab Erlangen-NürnbergVerifierad e-postadress på fau.de
Arne KüderlePhD Student, Machine Learning and Data Analytics Lab, FAU ErlangenVerifierad e-postadress på fau.de
Patrick KuglerResearcher at the Pattern Recognition Lab, University of Erlangen-NurembergVerifierad e-postadress på cs.fau.de
Felix KlugeBiomedical Research, Novartis Pharma AGVerifierad e-postadress på novartis.com
Heike LeutheuserProfessor for AAL & Medical Assistance Systems, University of BayreuthVerifierad e-postadress på uni-bayreuth.de
Robert RicherMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-NürnbergVerifierad e-postadress på fau.de
Jürgen WinklerProfessor für Neurologie, Universitätsklinikum ErlangenVerifierad e-postadress på uk-erlangen.de
Cristian PasluostaResearch Group Leader, University of FreiburgVerifierad e-postadress på imtek.uni-freiburg.de
Dominik SchuldhausDigital Sports Group, University of Erlangen-Nürnberg (FAU)Verifierad e-postadress på fau.de
Stefan GradlFriedrich-Alexander University Erlangen-Nürnberg (FAU)Verifierad e-postadress på fau.de
Julius HanninkFriedrich-Alexander University Erlangen-Nürnberg (FAU)Verifierad e-postadress på fau.de
Ulf JensenResearcher at the Pattern Recognition Lab, University of ErlangenVerifierad e-postadress på informatik.uni-erlangen.de
Thomas KautzMachine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-NürnbergVerifierad e-postadress på fau.de
Nils RothPhD Student, Machine Learning and Data Analytics LabVerifierad e-postadress på fau.de
Franz MarxreiterDr. med.Verifierad e-postadress på uk-erlangen.de
Dario ZancaHead of Applied Machine Learning Group @ MaD Lab, Friedrich-Alexander-Universität Erlangen-NürnbergVerifierad e-postadress på fau.de
Joachim HorneggerProfessor of Computer Science, Friedrich-Alexander-Universität Erlangen-NürnbergVerifierad e-postadress på fau.de
Christine F. MartindaleFriedrich-Alexander University Erlangen-NürnbergVerifierad e-postadress på fau.de

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Bjoern M. Eskofier

MaD Lab, FAU Erlangen-Nürnberg & TDH Group, Helmholtz Munich

Verifierad e-postadress på fau.de - Startsida

Machine Learning Artificial Intelligence Wearable Computing Digital Health Biomedical Eng


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
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	678	2016
Federated learning for healthcare: Systematic review and architecture proposal RS Antunes, C André da Costa, A Küderle, IA Yari, B Eskofier ACM Transactions on Intelligent Systems and Technology (TIST) 13 (4), 1-23, 2022	430	2022
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	395	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	368	2014
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	361	2017
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	315	2018
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	292	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	290	2013
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	241	2013
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	234	2018
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	225	2012
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	224	2015
Activity recognition in beach volleyball using a Deep Convolutional Neural Network: Leveraging the potential of Deep Learning in sports T Kautz, BH Groh, J Hannink, U Jensen, H Strubberg, BM Eskofier Data Mining and Knowledge Discovery 31, 1678-1705, 2017	207	2017
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	205	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	203	2016
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	197	2011
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	166	2017
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	159	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	148	2017
Estimation of gait kinematics and kinetics from inertial sensor data using optimal control of musculoskeletal models E Dorschky, M Nitschke, AK Seifer, AJ van den Bogert, BM Eskofier Journal of biomechanics 95, 109278, 2019	138	2019

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