Prof. Bjoern Eskofier, PhD

Machine Learning and Data Analytics (MaD) Lab

Friedrich-Alexander-Universität Erlangen-Nürnberg

Wearable Computing and Machine Learning for Digital Health and Precision Medicine



   The fast-growing costs of acute care are pushing the healthcare systems worldwide to a limit. Globally, we are coming to realize that we cannot afford to provide everybody with access to unlimited healthcare services in the light of current demographic changes. An alternative approach is emerging that focuses on “keeping people healthy” through primary and secondary prevention in all phases of life. This paradigm shift in the healthcare systems is demanding research in ambient, sensor-enhanced assistive technologies that “keep people outside of the hospital”. Therefore, a fast-growing interest exists for wearable and pervasive computing systems and ambient assistive technology that aim at ubiquitous health support for individuals in the home and community settings.


   The talk will present research projects (c.f. Fig. 1) where we implemented ambient sensors for physiological and biomechanical data recording, used pervasive computing systems for monitoring and signal processing, and employed machine learning algorithms and simulation models in order to provide accurate information to patients and caregivers in neurological and musculoskeletal movement disorders with the aim of promoting quality of life of patients and improving health care.


   As a model disease for technology development, Parkinson’s disease (PD) will be presented. Routinely assessed by observation, the disease’s symptoms are rated as part of semiquantitative clinical scores. In an alliance between medicine and engineering, a sensor based gait analysis system that objectively assesses gait patterns in PD was developed. The system provides spatiotemporal gait parameters and was evaluated in PD patients (n=190) and age-matched controls (n=101). Cross-sectional analysis revealed altered gait parameters and variations represented by short steps, shuffling gait, and postural instability in PD patients that were specific for different disease stages. In addition, gait parameters reflecting the progressive nature of PD corresponded to physician ratings of gait impairment over time. These data demonstrated the feasibility and applicability of more objective sensor-based gait measurement in PD for clinical studies and individual patient care.


   The outlook of the presentation will focus on future research directions that aim at contributing to the above mentioned paradigm shift in global healthcare systems by the use of wearable and pervasive computing for digital health support and precision medicine.




Fig. 1: The miLife research project for the application of wearable computing systems and machine learning algorithms in sports and medicine.




Short Biography


   Bjoern M. Eskofier is German Research Foundation (DFG) funded Heisenberg-Professor for "Digital Support Systems in Sports and Medical Engineering" and endowed professor of the Adidas AG. He heads the Machine Learning and Data Analytics (MaD) Lab and the Central Institute for Medical Engineering at the Friedrich-Alexander-University Erlangen-Nuernberg (FAU). Currently, his lab has 30 co-workers, who research in the fields of machine learning and signal analysis for wearable computing systems in sports and health care. The motivation of the lab’s researchers is to increase human wellbeing.

   Dr. Eskofier studied Electrical Engineering at the FAU and graduated in 2006. He then studied under the supervision of Prof. Dr. Benno Nigg at the University of Calgary (Canada). There, he received his PhD degree in Biomechanics in 2010 for his research on "Application of Pattern Recognition Methods in Biomechanics". He authored more than 160 peer reviewed articles, submitted 5 patent applications, and started three spinoff startup companies. He won several medical-technical research awards. In 2016, he was a visiting professor in Dr. Paolo Bonato’s Motion Analysis Lab at Harvard Medical School (February-March), and in 2018, he was a visiting professor in Dr. Alex “Sandy” Pentland’s Human Dynamics group at MIT Media Lab (March-August). He is also a delegate of the FAU to the Medical Valley (80 Mio Euro German Ministry of Education funded cluster) and to the European Institute of Innovation & Technology for Health (EIT Health, 500 Mio Euro EU consortium, 2015-2021).

   Bjoern Eskofier has defined his research and entrepreneurial agenda to revolve around contributions to a “Digital Health Ecosystem”, where patients are connected to other stakeholders within the Healthcare system using digital support tools. His digital health research philosophy is that only multidisciplinary teams of engineers, medical experts, industry representatives and entrepreneurs will have the tools to actually implement changes in Healthcare.



   Presenter: Hemda Garelick is a Professor of Environmental Science and Public Health Education at Middlesex  University, London, and has worked on the topic for many years, in collaboration with Prof Diane Purchase and a team of researchers.

   Prof  Garelick is the President of the ‘Chemistry and the Environment’  Division of the International Union of Pure and Applied Chemistry (IUPAC) https://iupac.org/who-we-are/divisions/division-details/?body_code=600  .

   The Division has led a review project on the  ‘The Environmental and Health Challenges of E-Waste and its Management: An Emerging 21st Century Global Concern’ https://iupac.org/projects/project-details/?project_nr=2014-031-3-600. This project has been accepted for publication in the journal Pure and Applied Chemistry.


   Hemda Garelick is a Professor of Environmental Science and Public Health Education, Department of Natural Sciences, School of Science and Technology, Middlesex University. She is currently the President of ‘Chemistry and the Environment’ Division at the International Union of Pure and Applied Chemistry (IUPAC). https://iupac.org/who-we-are/divisions/division-details/?body_code=600

   Prof Garelick has a long term interest in public and environmental health, with particular focuses on health and hygiene aspects of water, wastewater and sanitation systems, investigating of health aspects of chemical and microbial pollution in water and soil. Areas of particular interest include: the analysis and the fate of antibiotics and antibiotic resistant microorganisms in the environment and in food, as well as the impact of solid waste disposal such as electronic waste (E-Waste) and its effect. Her interest in pollution affecting poor societies has also led her to investigate the problem of arsenic pollution in drinking water and the effect of people exposure to contaminated groundwater. Similarly she became interested in the informal recycling of electronic waste (E-Waste) and its effect on the health and environment of poor societies such as the Nigerian sites near the city of Lagos.

   As well as the research carried out at Middlesex University a number of IUPAC projects related to the above have been developed and carried out.






   Guger Christoph studied electrical and biomedical engineering at the University of Technology Graz in Austria and Johns Hopkins University in the USA and received his PhD in 1999. In 1999 he started the company g.tec which was now branches in Austria, Spain, the USA and Hong Kong. g.tec produces high-quality neurotechnology and real-time brain computer interfaces for the research, medical and consumer market. The company is active in many international research projects about brain-computer interfacing, neuromodulation, stroke rehabilitation, assessment and communication with patients with disorders of consciousness and high-gamma mapping in epilepsy and tumor patients.

Title: Current and future applications of brain-computer interfaces

   Brain-computer interfaces are realized with EEG and ECoG recordings and are extracting in real-time information of the brain. In the talk the major principles like motor imagery, P300 and SSVEP will be explained. Furthermore, it will be shown how to use neurotechnology for stroke rehabilitation, brain assessment, communication and control applications and how to setup closed-loop experiments including invasive and non-invasive brain and body stimulation.

   We are running a Summer School and BCI Hackthon from 29th of June until 3rd of July and therefore I am often blocked: https://www.gtec.at/summer-school-2020/ Maybe you can cross-link your attendees also to our conference if you find some talks or the BCI Hackathon interesting before or after the conference.







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