Development of a self-learning machine learning pipeline for a mobile application supporting sports activity

  • Subject:AI, artificial intelligence, vital data, vital sensors, sleep research
  • Type:Bachelor- / Masterarbeit
  • Date:ab 06 / 2023
  • Tutor:

    M.Sc. Gergely Biri

  • Zusatzfeld:

    Abschlussarbeit m FZI.

Development of a self-learning machine learning pipeline for a mobile application supporting sports activity


In our Medical Information Technology (MIT) department, we are involved in several research projects related to wearable biosensors. As an intern or university student, you would have the opportunity to work with vital sensor data and apply your technical skills to develop innovative algorithms using machine learning.

The goal of our research project is to implement a self-learning prediction model based on multimodal data sources (acceleration measurement, e-daily rating, GPS signals) using machine learning methods, which can be used to determine the correct trigger time for a behavior change.

In this research project, you will work on cutting-edge technologies in sports and health sciences using advanced biosensor data (ECG, accelerometer, barometer, thoracic impedance, etc.) from wearable sensors to detect physical activity and improve sleep quality. Whether you're interested in machine learning or cutting-edge wearable sensor technology, you'll have the opportunity to contribute to the development of innovative systems that can revolutionize the way we classify activity and analyze sleep using wearable sensors.

Join our team and make a real impact on the world through your research and development efforts!


  • You will start with your own research to be up-to-date on the latest wearable technologies in the field of neural networks and vital signal analysis.
  • You will have the opportunity to steer your research topic in a new direction according to your own prior knowledge or interests.
  • You will analyse real-world data from ambulatory assessments to improve healthcare decision-making.
  • You will design and implement algorithms for the analysis of bio-signal data with conventional and spiking neural networks.
  • You will work with our research team on projects in the field of data analysis and bio signal data.


  • You are studying electrical engineering or information technology (bachelor's or master's)
  • You are interested in the topic and (possibly) have initial experience with artificial intelligence and/or bio signal data.
  • You have good programming skills and experience with Python programming language and its AI tools.
  • You are motivated and have good communication skills.
  • You have good written and spoken English and/or German skills.