Seminar: Earables in Automated Dietary Monitoring and Digital Health

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Novel wireless in-ear headphones can do more than playing music. They come with various types of sensors, e.g. microphones, or inertial measurement unit (IMU). In past research, earables have been used to monitor dietary activity in free living using microphones, which capture e.g. chewing sounds. The goal of this seminar is to get familiar with the possibilities of earables in automated dietary monitoring (ADM) and digital health, and to develop a machine learning algorithm for e.g. chewing event detection, and to deploy it to an existing app using e.g. Tensorflow Lite.


Investigate usefulness of earables in ADM contexts; Develop algorithms for biomarker processing of sensor data; App development

Learning Objectives:

  • Understand different sensor types and their digital health applications
  • Develop algorithms for biomarker processing
  • Deploy deep learning algorithms to apps


Project type Seminar
ECTS  2.5, 5, 7.5
Language English and/or German
Period Winter term 2021/22
Presence time Virtual seminar, working from remote
Useful knowledge Signal Processing and machine learning in Python, App programming in Flutter/native
Work distribution 20% data investigation and literature research 80% programming in Python
Med. Eng. designation Advanced Context Recognition (ACR)
StudOn link Link will follow shortly.
First meeting Online introduction/Vorbesprechung
Registration Via StudOn, obligatory after introduction.



Up-to-date literature recommendations are provided during the meetings.


Final presentation and final report.


David Kopyto

  • Job title: Researcher
  • Address:
    Henkestraße 91, Haus 7, 1. OG
    91052 Erlangen
  • Phone number: +49 9131 85-23608
  • Email:

Friedrich-Alexander-Universität Erlangen-Nürnberg