A HIGH-SPEED BRAIN SPELLER USING STEADY-STATE VISUAL EVOKED POTENTIALS

TLDR

SSVEP‑based BCIs face challenges in stimulus presentation and target identification, complicating complex spelling programs. The study investigates whether mixed frequency and phase coding can enable a high‑speed SSVEP speller on a computer monitor. A frequency‑and‑phase approximation creates 32 flickers using eight frequencies (8–15 Hz) and four phases, while a multi‑channel CCA method with SSVEP training data identifies targets. In a simulated online experiment, the speller achieved an average ITR of 166.91 bits/min (max 192.26 bits/min) at 40 cpm, the highest ever reported for EEG‑based BCIs, demonstrating strong potential for real‑life applications.

Abstract

Implementing a complex spelling program using a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) remains a challenge due to difficulties in stimulus presentation and target identification. This study aims to explore the feasibility of mixed frequency and phase coding in building a high-speed SSVEP speller with a computer monitor. A frequency and phase approximation approach was developed to eliminate the limitation of the number of targets caused by the monitor refresh rate, resulting in a speller comprising 32 flickers specified by eight frequencies (8-15 Hz with a 1 Hz interval) and four phases (0°, 90°, 180°, and 270°). A multi-channel approach incorporating Canonical Correlation Analysis (CCA) and SSVEP training data was proposed for target identification. In a simulated online experiment, at a spelling rate of 40 characters per minute, the system obtained an averaged information transfer rate (ITR) of 166.91 bits/min across 13 subjects with a maximum individual ITR of 192.26 bits/min, the highest ITR ever reported in electroencephalogram (EEG)-based BCIs. The results of this study demonstrate great potential of a high-speed SSVEP-based BCI in real-life applications.