Seminar: Earables in Automated Dietary Monitoring and Digital Health
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
- Understand different sensor types and their digital health applications
- Develop algorithms for biomarker processing
- Deploy deep learning algorithms to apps
|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.