About this document
A Real-Time ML-based Asynchronous HCI Speller System Using EOG Signals by mustafa hayawi is a document available to read on EtoBox.
The document presents a real-time, machine learning-based asynchronous human-computer interface (HCI) speller system utilizing electrooculogram (EOG) signals to assist individuals with communication challenges. This system allows users to select from 45 targets displayed on a screen through eye movements, achieving a classification precision of 100% and an information transfer rate of 275.47 bits/min in experiments with healthy participants. The proposed solution is low-cost, portable, and user-friendly, en
- Author
- mustafa hayawi
- Language
- EN