The SIPPRE Research Group is pleased to announce a new diploma thesis position focusing on the integration of Brain-Computer Interfaces (BCI) with consumer-grade smartwatches.
Thesis Overview
The project aims to develop a real-time brain signal monitoring system that streams processed EEG data from BCI devices to consumer smartwatches. The system will provide immediate biometric feedback, such as frequency band power visualization (Alpha, Beta, Theta), through an intuitive wearable interface.
Hardware Platforms
BCI Devices: EmotiBit, OpenBCI Cyton/Ganglion, or Enophone
Smartwatches: Google Pixel Watch 2 or Samsung Galaxy Watch7 (provided)
System Design
A hybrid architecture will be explored, involving:
Signal acquisition via BCI hardware
Real-time processing (filtering, FFT, band power extraction) using the Brainflow framework
Data distribution through an Android application
Wear OS visualization on a smartwatch with custom UI for live feedback
An alternative, mobile-only implementation will also be considered to eliminate the PC dependency.
Research Goals
Demonstrate feasibility of BCI-smartwatch integration
Evaluate user experience and interface design for biometric feedback
Benchmark system latency and reliability
Explore applications in meditation, sleep analysis, focus training, and cognitive load assessment.
Expected Outcomes
A fully functional prototype system (open-source)
Benchmarks on performance and latency
User interface design guidelines for wearable biometric displays
Academic contributions on the use of consumer wearables in BCI research
Innovation Potential
This project bridges professional-grade BCI technology with everyday consumer wearables, paving the way for more accessible neurotechnology in wellness and cognitive training applications.