Wearable EEG patch records stable brain signals over 24 hours, including sleep
Reliably recording brain activity over many hours has so far been fraught with technical and practical challenges. While traditional electroencephalography (EEG) systems provide meaningful data, they are often uncomfortable and typically limited to controlled testing environments. Is it even possible to record EEG signals with good signal quality in everyday situations?
A flexible, eight-channel EEG patch, known as the trEEGrid, developed at the Fraunhofer Institute for Digital Media Technology in Oldenburg, has successfully recorded stable brain signals for nearly 24 hours, including sleep. This patent-pending patch, which can be applied like a Band-Aid without exerting pressure on the head, was worn by 10 participants throughout the study.
The patch is connected to a miniaturized signal amplifier, which is attached to the patch behind the ear, reducing interference from cable movement. Power is supplied by a waist or chest pocket unit, minimizing restrictions to movement. The study employed several short auditory and visual stimulation tasks, relaxation exercises, and Sudoku puzzles, with participants also going about their daily lives.
Despite overnight recording, the electrode patch remained securely in place, maintaining very stable contact throughout the period. Impedance values, which indicate the quality of the connection between the electrodes and the skin, averaged below 140 kOhm on the first day and even below 100 kOhm on the second day. The system's ability to distinguish between different Sudoku task difficulties demonstrated its potential for real-world applications in health monitoring, including sleep disorder detection, daytime sleepiness research, and neurological disease studies.
The Fraunhofer IDMT is now expanding the tests to a more diverse group of participants and dynamic everyday situations. The goal is to develop AI-based methods for interpreting and automatically filtering out interference signals, opening up new possibilities for analyzing brain activity data in various settings.
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