top of page

BrainEReader

Time: Aug 2015 - Present

Individual Project

My Role: Software & Interaction Design

cap5
cap4
cap3
cap2
exp1
open
System Design

E-books become increasingly convenient and popular nowadays. However, most e-book viewer applications with traditional computer interface are not accessible for people with severe motor disabilities. This project aims to develop a user-friendly e-book viewer with brain computer interface (BCI) to assist those people to read an e-book.

 

The BCI system is designed to acquire the EEG data, extract features from the data, classify the data and use the classification result to control the page turning. A customer-grade Electroencephalography (EEG) device called Mindwave Mobile from NeuroSky is used to detect the brainwave data from users. Experiments on blinking, motor imagery, color and eye states have been conducted to find out the best way to analyze a user’s mental states recorded by the single dry-contact EEG electrode at Fp1. The final solution is to use the fast Fourier transform (FFT) and a signal quantization method to transform brainwave raw data into feature vectors, classify the data by a linear Support Vector Machine (SVM) model and select blinking and eye states (eyes opening and closing) as the brain control.

 

It has been tested that users can use this e-book viewer to turn pages to the previous and next by keeping eyes closed and open respectively with over 95% accuracy.

bottom of page