EEG-based action anticipation in human-robot interaction: a comparative pilot study
Rodrigo Vieira, Plinio Moreno, Athanasios Vourvopoulos · 2024
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Description
Rodrigo Vieira, Plinio Moreno, and Athanasios Vourvopoulos test brain signals for predicting human action in a 2024 pilot study. The setting is human-robot teamwork, where a robot that sees a move coming can work more safely. Brain waves, read by EEG sensors on the scalp, can show signs of a planned move more than a second before it happens.
The team trained deep learning models on a data set where people imagined movements. Their best model sorted the signals with accuracy near eighty-one percent. In a live pilot test, actions were forecast a few hundred milliseconds before they were carried out. The authors say pairing brain signals with modern learning methods could make shared tasks smoother. They frame the work as an early step toward safer joint work with robots.
Catalog record
| CREATOR | Rodrigo Vieira, Plinio Moreno, Athanasios Vourvopoulos |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |