An E-Book Viewer with Automatic Page Turning Controlled by Analyzing Brainwave

Abstract

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. This report discusses the design, implement and testing of a BCI system. The result is an e-book viewer application that users can turn pages to the previous and next by keeping eyes closed and open respectively with over 97% accuracy, which can inform the design of BCI applications with the MindWave Mobile that can benefit people with severe motor disabilities.