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Brain-Computer Interface for Password Input: Enhancing Accessibility for Individuals with Mobility Impairments

Researchers will develop password technology for those with mobility impairments, harnessing Brain-Computer Interface (BCI) systems to create a machine learning system using portable electroencephalogram (EEG) headsets to extract passwords from users’ brain signals. 

Funded by the CCI Hub


Project Investigators

Rationale and Background

Password security is paramount in digital interactions. However, individuals with mobility impairments, such as paralysis, limited dexterity, or motor disabilities, face obstacles with traditional password input methods.

Integrating BCI into password technology improves the accessibility of password-protected systems while empowering individuals with mobility impairments to navigate the digital landscape. 

Methodology

Researchers will focus on developing technologies that are user-friendly and intuitive, regardless of users’ background or level of expertise. 

They’ll innovate new technologies to improve password bit rate by leveraging the Ultracortex Mark IV, a recently introduced device featuring improved electrode placements on the head, enhancing the quality of EEG signals. 

Researchers will also leverage sophisticated machine learning algorithms to train a model and accurately identify the box at which the user is gazing. 

Projected Outcomes

Researchers will build a high-rate steady state visual evoked potential SSVEP-based BCI system with portable devices. The BCI system consists of an inexpensive EEG device and a laptop or a smartphone, which are portable and friendly for personal use. 

Following this project, they will submit their proposal to potential funding opportunities, including: