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Computer Science

D-Index
42
Citations
7327
World Ranking
8398
National Ranking
409

Research.com Recognitions

  • 2020 - ACM Senior Member

Overview

Bjoern M. Eskofier is affiliated with the University of Erlangen-Nuremberg in Germany. Their research primarily focuses on the field of medicine, with a distinct concentration on biomedical engineering, artificial intelligence, computer vision and pattern recognition, physical therapy, sports therapy and rehabilitation, and cognitive neuroscience.

Their work covers several key topics, including:

  • Balance, Gait, and Falls Prevention
  • Cerebral Palsy and Movement Disorders
  • Muscle activation and electromyography studies
  • EEG and Brain-Computer Interfaces
  • Non-Invasive Vital Sign Monitoring
  • Parkinson's Disease Mechanisms and Treatments
  • Gait Recognition and Analysis

Eskofier has contributed frequently to a variety of publication venues. The most common platforms for their work include:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Sensors
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Psychoneuroendocrinology

Among their recent papers are the following:

  • "Federated Learning for Healthcare: Systematic Review and Architecture Proposal," 2022, ACM Transactions on Intelligent Systems and Technology
  • "Advancing digital health applications: priorities for innovation in real-world evidence generation," 2022, The Lancet Digital Health
  • "CNN-Based Estimation of Sagittal Plane Walking and Running Biomechanics From Measured and Simulated Inertial Sensor Data," 2020, Frontiers in Bioengineering and Biotechnology
  • "Technical validation of real-world monitoring of gait: a multicentric observational study," 2021, BMJ Open
  • "Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium," 2023, Journal of NeuroEngineering and Rehabilitation

Their frequent co-authors include:

  • Arne Küderle
  • Felix Kluge
  • Dario Zanca
  • Robert Richer
  • Jochen Klucken

Bjoern M. Eskofier was awarded the title of ACM Senior Member in 2020.

Best Publications

  • Technology in Parkinson's disease: Challenges and opportunities.

    Alberto J. Espay;Paolo Bonato;Fatta B. Nahab;Walter Maetzler

  • An Emerging Era in the Management of Parkinson's Disease: Wearable Technologies and the Internet of Things

    Cristian F. Pasluosta;Heiko Gassner;Juergen Winkler;Jochen Klucken

  • Wearable sensors objectively measure gait parameters in Parkinson's disease.

    Johannes C. M. Schlachetzki;Jens Barth;Franz Marxreiter;Julia Gossler

  • Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems.

    Mohamed Elgendi;Björn Eskofier;Socrates Dokos;Derek Abbott

  • Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset

    Heike Leutheuser;Dominik Schuldhaus;Bjoern M. Eskofier

  • Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices

    Stefan Gradl;Patrick Kugler;Clemens Lohmuller;Bjoern Eskofier

  • Sensor-Based Gait Parameter Extraction With Deep Convolutional Neural Networks.

    Julius Hannink;Thomas Kautz;Cristian F. Pasluosta;Karl-Gunter Gasmann

  • Recent machine learning advancements in sensor-based mobility analysis: Deep learning for Parkinson's disease assessment

    Bjoern M. Eskofier;Sunghoon I. Lee;Jean-Francois Daneault;Fatemeh N. Golabchi

  • Activity recognition in beach volleyball using a Deep Convolutional Neural Network

    Thomas Kautz;Benjamin H. Groh;Julius Hannink;Ulf Jensen

  • An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring

    Bjoern M. Eskofier;Sunghoon Ivan Lee;Manuela Baron;André Simon

  • Estimation of gait kinematics and kinetics from inertial sensor data using optimal control of musculoskeletal models

    Eva Dorschky;Marlies Nitschke;Ann-Kristin Seifer;Antonie J. van den Bogert

  • CNN-Based Estimation of Sagittal Plane Walking and Running Biomechanics From Measured and Simulated Inertial Sensor Data.

    Eva Dorschky;Marlies Nitschke;Christine F. Martindale;Antonie J. van den Bogert

  • Mobile Stride Length Estimation With Deep Convolutional Neural Networks

    Julius Hannink;Thomas Kautz;Cristian F. Pasluosta;Jens Barth

  • An approximation of the Gaussian RBF kernel for efficient classification with SVMs

    Matthias Ring;Bjoern M. Eskofier

  • Temporal Trajectory Aware Video Quality Measure

    M. Barkowsky;J. Bialkowski;B. Eskofier;R. Bitto

  • Sensor-based stroke detection and stroke type classification in table tennis

    Peter Blank;Julian Hoßbach;Dominik Schuldhaus;Bjoern M. Eskofier

  • Support vector machines for detecting age-related changes in running kinematics $

    Reginaldo K. Fukuchi;Bjoern M. Eskofier;Marcos Duarte;Reed Ferber

  • Promoting relaxation using virtual reality, olfactory interfaces and wearable EEG

    Judith Amores;Robert Richer;Nan Zhao;Pattie Maes

  • Pattern classification of kinematic and kinetic running data to distinguish gender, shod/barefoot and injury groups with feature ranking

    Bjoern M. Eskofier;Martin Kraus;Jay T. Worobets;Darren J. Stefanyshyn

  • Generic performance measure for multiclass-classifiers

    Thomas Kautz;Bjoern M. Eskofier;Cristian F. Pasluosta

  • Promoting relaxation using virtual reality, olfactory interfaces and wearable EEG

    Judith Amores Fernandez;Robert Richer;Nan Zhao;Patricia Maes

Frequent Co-Authors

Jürgen Winkler
Jürgen Winkler University of Erlangen-Nuremberg
Andreas Maier
Andreas Maier University of Erlangen-Nuremberg
Olaf Riess
Olaf Riess University of Tübingen
Nicolas Rohleder
Nicolas Rohleder University of Erlangen-Nuremberg
Joachim Hornegger
Joachim Hornegger University of Erlangen-Nuremberg
Martin Burger
Martin Burger University of Erlangen-Nuremberg
Antonie J. van den Bogert
Antonie J. van den Bogert Cleveland State University
Derek Abbott
Derek Abbott University of Adelaide
Rebecca Fahrig
Rebecca Fahrig Siemens Healthcare (United States)
Florencia Labombarda
Florencia Labombarda University of Buenos Aires

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