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A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling
Pieter-Jan Kindermans · Hannes Verschore · David Verstraeten · Benjamin Schrauwen

Mon Dec 03 07:00 PM -- 12:00 AM (PST) @ Harrah’s Special Events Center 2nd Floor #None

The usability of Brain Computer Interfaces (BCI) based on the P300 speller is severely hindered by the need for long training times and many repetitions of the same stimulus. In this contribution we introduce a set of unsupervised hierarchical probabilistic models that tackle both problems simultaneously by incorporating prior knowledge from two sources: information from other training subjects (through transfer learning) and information about the words being spelled (through language models). We show, that due to this prior knowledge, the performance of the unsupervised models parallels and in some cases even surpasses that of supervised models, while eliminating the tedious training session.

Author Information

Pieter-Jan Kindermans (Ghent University)
Hannes Verschore (Ghent University)
David Verstraeten (Ghent University)
Benjamin Schrauwen (Ghent University)

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