Seminar: Automatic Labelling for Chewing Timeseries
Course/Project description
Chewing is an essential component of eating. Chewing cycles can be recorded using various sensors and detected applying appropriate algorithms. However, evaluating a chewing detection algorithm is usually difficult due to the lack of accurate ground truth. It is even more difficult to label free-living data of a tremendous number of chewing cycle instances. Based on our investigation, Temporalis electromyography (EMG) can serve as a reliable source of ground truth among a few other choices, e.g. videos and dietary diaries. The proposed student project aims at providing an accurate automatic chewing cycle labelling tool for EMG signals. The onsets and offsets of chewing cycles shall be detected and labelled. The labelling tool will be implemented in Python. The automatic labelling performance will be also evaluated compared with manual labels.
Learning objectives
- Python and graphical programming
- Timeseries processing and chewing detection
Course data
| ECTS | 2.5, 5, 7.5, default: 5 |
| Project type | BSc./MSc.-Seminar, Thesis |
| Language | English |
| Presence time | 4 SWS |
| Useful knowledge | Python, timeseries processing |
| Work distribution | 100% programming |
| Period | Summer semester 2019 |
| First meeting | Seminar introduction on
24. Apr. 2019, 17:00-18:30 at Henkestr. 91, Haus 7, 1. OG, R 373. |
Literature
Up-to-date literature recommendations are provided during the lectures.
Examination
Final presentation and final report.
Contact
Rui Zhang
- Job title: Researcher
- Address:
Henkestr. 91, Geb. 7
91052 Erlangen - Phone number: +49 9131 85-23604
- Email: rui.rui.zhang@fau.de