Seminar or Thesis: Unobtrusive Continuous Sleep Monitoring with Wearable Accessory

Creative Commons CC0 license.

Bachelor/Master Thesis, Seminar

Course description

Sleep is a natural recovering mechanism, implying behaviour during the night. Quality of sleep has an impact on daily life and is indicator for general health. Automatic sleep assessment without conditioning the patient status is a grand-challenge for the state-of-the-art technology. This seminar will consider physiological, technological and data-analytics aspects with the aim to develop an unobtrusive wearable sensor-based solution for sleep-related behavioural and physiological pattern continuous monitoring.

Learning Objectives

  • Gain overview on state-of-the-art of wearable technology for sleep monitoring.
  • Understand physiological principles behind the sleep mechanism.
  • Design a wearable sensor setup.
  • Implement an experimental protocol for data collection.
  • Create machine-learning algorithms for signal processing and data abstraction.
  • Team work.

Course data

ECTS 4
Project type BSc./MSc.-Seminar (Group work), Thesis
Language English
Presence Time Lecture: 2 SWS, Exercise: 2 SWS
Useful knowledge Human Physiology Principles, Signal Processing, Machine Learning
Period Immediate
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Contact

Giovanni Schiboni

Friedrich-Alexander-Universität Erlangen-Nürnberg