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Bjoern M. Eskofier
Bjoern M. Eskofier
MaD Lab, FAU Erlangen-Nürnberg & TDH Group, Helmholtz Munich
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Zitiert von
Zitiert von
Jahr
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
6242016
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
3712015
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
3432014
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
3222017
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
2852018
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
2792014
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
2732013
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
2582022
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
2282013
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
2222012
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
2122015
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
1992018
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
1882016
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
1872016
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
1872011
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
1822017
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
1552017
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
1452017
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
1362017
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
1192019
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