Bachelor/Master Thesis: Gesture Recognition with the OpenEarable

Background

Earables are earbuds that are equipped with multiple sensors. Among them, the OpenEarable (Röddiger et al., 2024) stands out as the device with the most sensors globally, enabling a wide range of interaction possibilities. While interaction with earables has been extensively explored in literature (Röddiger et al., 2022), the OpenEarable’s advanced sensor suite offers the unique potential to detect multiple types of gestures simultaneously and in real-time.
This thesis project focuses on leveraging the OpenEarable’s capabilities to expand gesture-based interaction possibilities. The specific goals of the thesis are outlined as follows:

Tasks

BA/MA:

1. Developing a set of distinct gestures that can be detected in real-time using the OpenEarable.
2. Option to focus specifically on hands-free gestures.

MA additional:

1. Implementing and deploying gesture recognition algorithms directly onto the OpenEarable device.
2. Designing gestures that utilize multiple sensors in combination, demonstrating the added value of multi-sensor interaction.
3. Showcase the practical potential of the developed gestures through compelling use-case demonstrations

Requirements

• Interest in Human-Computer-Interaction (HCI) and the real-world application of new devices
• Good Python skills
• Optional (mainly for MA)
  • Good C/C++ skills
  • Experience with Arduino

If you are interested in this topic, please contact Jonas Hummel (hummel@teco.edu)