Leveraging Deep Neural Networks for Lucid Dream Communication via Two-Dimensional Electrooculography
PsyArXiv December 21, 2023 preprint DOI: 10.31234/osf.io/cxwka (opens in new tab)
Summary
AI-generated from the abstractA method using deep neural networks to interpret two-dimensional electrooculography signals enables real-time communication from within lucid dreams. The approach allows dreamers to convey information by moving their eyes in specific patterns, which the network decodes with high accuracy. This technique opens new possibilities for studying dream content and for interactive dream applications.
Study at a glance
| Key finding | Deep neural networks can decode two-dimensional electrooculography signals from lucid dreamers to enable real-time communication. |
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Abstract
Leveraging Deep Neural Networks for Lucid Dream Communication via Two-Dimensional Electrooculography