The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm

Yeou-Jiunn Chen,Shih-Chung Chen,Chung-Min Wu,Pei-Jarn Chen,Andrew Jason Tickle,Ilham A E Zaeni

doi:10.1155/2015/234260

Abstract

The so-called amyotrophic lateral sclerosis (ALS) or motor neuron disease (MND) is a neurodegenerative disease with various causes. It is characterized by muscle spasticity, rapidly progressive weakness due to muscle atrophy, and difficulty in speaking, swallowing, and breathing. The severe disabled always have a common problem that is about communication except physical malfunctions. The steady-state visually evoked potential based brain computer interfaces (BCI), which apply visual stimulus, are very suitable to play the role of communication interface for patients with neuromuscular impairments. In this study, the entropy encoding algorithm is proposed to encode the letters of multilevel selection interface for BCI text input systems. According to the appearance frequency of each letter, the entropy encoding algorithm is proposed to construct a variable-length tree for the letter arrangement of multilevel selection interface. Then, the Gaussian mixture models are applied to recognize electrical activity of the brain. According to the recognition results, the multilevel selection interface guides the subject to spell and type the words. The experimental results showed that the proposed approach outperforms the baseline system, which does not consider the appearance frequency of each letter. Hence, the proposed approach is able to ease text input interface for patients with neuromuscular impairments.

Highlights

The neurodegenerative disease or spinal cord injury always reduces the muscle ability and results in difficulties in speaking, swallowing, and breathing
The letters used in this state visually evoked potential (SSVEP)-based brain computer interface (BCI) text input system can be categorized into four groups, including 26 uppercase letters, 26 lowercase letters, 10 numbers, and 4 special letters
It is clear that the accuracy of 4 kinds of visual stimulation frequencies from 6 Hz to 9 Hz was higher than 85% and it can be applied to a practical application

Summary

Introduction

The neurodegenerative disease or spinal cord injury always reduces the muscle ability and results in difficulties in speaking, swallowing, and breathing. The life quality of people with the above disease is always greatly reduced. It would make them find difficulty in performing even simple activities, such as communicating with other people. These severely disabled lost many human functions, they still have healthy eyes and brain which can help them see and think. In order to better provide the needs of these severely disabled, a lot of high technology assistive devices have been developed in recent years. There is an interactive method by brain computer interface (BCI) technology proposed in this paper to help the disabled communicate with other people

Methods

Results

Conclusion