Phase-Approaching Stimulation Sequence for SSVEP-Based BCI: A Practical Use in VR/AR HMD

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Steady-state visual evoked potential (SSVEP) offers high information transfer rate (ITR) and accuracy for brain-computer interfaces (BCI).
• Head-mounted devices (HMDs) are increasingly used for SSVEP-based BCIs, but their fixed frame rates limit available stimulation frequencies.
• This limitation restricts the number of commands achievable in HMD-based SSVEP BCIs.

Purpose of the Study:

• To propose a novel phase-approaching (PA) method for generating visual stimulation sequences at user-specified frequencies on HMDs.
• To overcome the frequency limitations imposed by the fixed frame rates of HMDs.
• To increase the number of available commands for SSVEP-based BCIs.

Main Methods:

• A phase-approaching (PA) method was developed to generate visual stimulation sequences (PAS sequences) approximating user-specified frequencies.
• The PA method minimizes the phase difference between the generated sequence and an ideal wave at the target frequency.
• Steady-state visual evoked potentials (SSVEPs) evoked by PAS sequences were analyzed using canonical correlation analysis (CCA) to identify the user's gazed target.

Main Results:

• A six-command SSVEP-based BCI was successfully implemented using the PA method to control a flying drone.
• The system achieved a high information transfer rate (ITR) of 36.84 bits/min.
• A high detection accuracy of 93.30% was recorded for identifying user commands.

Conclusions:

• The proposed phase-approaching (PA) method effectively increases the number of available commands for SSVEP-based BCIs on head-mounted devices (HMDs).
• This method overcomes the frequency limitations inherent in HMDs with fixed frame rates.
• The demonstrated performance indicates the potential of this PA method for practical BCI applications, such as controlling devices like flying drones.