Chair of Computer Science 14 – Machine Learning and Data Analytics

Overview

The researchers in the Machine Learning and Data Analytics (MaD) lab conduct theoretical and applied research for wearable computing systems and machine learning algorithms for engineering applications at the intersection of sports and health care. Our motivation is generating a positive impact on human wellbeing, be it through increasing performance, maintaining health, improving rehabilitation, or monitoring disease. Additionally, machine learning algorithms are studied in the context of industry 4.0.

People

You can find an overview of the complete MaD lab team here.

Research topics

The MaD Lab is organized in five research groups working on different interdisciplinary topics:

• Applied Machine Learning
• Biomechanical Motion Analysis and Creation
• Digital Health – Biosignals
• Digital Health – Gait Analytics
• Sport Analytics

Selected publications

• • Ullrich M., Küderle A., Hannink J., Del Din S., Gaßner H., Marxreiter F., Klucken J., Eskofier B., Kluge F.:
    Detection of Gait From Continuous Inertial Sensor Data Using Harmonic Frequencies
    In: IEEE Journal of Biomedical and Health Informatics 24 (2020), p. 1869 - 1878
    ISSN: 2168-2194
    DOI: 10.1109/JBHI.2020.2975361
    URL: https://www.mad.tf.fau.de/files/2020/11/2020_ullrich_gaitsequencedetection.pdf
• • Dorschky E., Nitschke M., Seifer AK., van den Bogert AJ., Eskofier B.:
    Estimation of Gait Kinematics and Kinetics from Inertial Sensor Data Using Optimal Control of Musculoskeletal Models
    In: Journal of Biomechanics (2019)
    ISSN: 0021-9290
    DOI: 10.1016/j.jbiomech.2019.07.022
    URL: https://www.mad.tf.fau.de/files/2019/08/201908_JBiomech_Dorschky.pdf
• • Dorschky E., Krüger D., Kurfess N., Schlarb H., Wartzack S., Eskofier B., van den Bogert AJ.:
    Optimal control simulation predicts effects of midsole materials on energy cost of running
    In: Computer Methods in Biomechanics and Biomedical Engineering (2019)
    ISSN: 1025-5842
    DOI: 10.1080/10255842.2019.1601179
    URL: https://www.mad.tf.fau.de/files/2019/08/201904_CMBBE_Dorschky.pdf
• • Haji Ghassemi N., Hannink J., Roth N., Gaßner H., Marxreiter F., Klucken J., Eskofier B.:
    Turning analysis during standardized test using on-shoe wearable sensors in parkinson’s disease
    In: Sensors 19 (2019), Article No.: 3103
    ISSN: 1424-8220
    DOI: 10.3390/s19143103
• • Löffler C., Riechel S., Fischer J., Mutschler C.:
    Evaluation Criteria for Inside-Out Indoor Positioning Systems Based on Machine Learning
    In: International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nantes, France: 2018
    DOI: 10.1109/ipin.2018.8533862
    URL: https://ieeexplore.ieee.org/document/8533862

Further information

More information about the MaD lab can be found on the website.