مقاله انگلیسی رایگان در مورد رابط مغز و رایانه – IJCAonline 2017

Brain Computer Interface (BCI) is often directed at mapping, assisting, or repairing human cognitive or sensory-motor functions. Electroencephalogram (EEG) is a non-invasive method of acquisition brain electrical activities. Noises are impure the EEG recorded signal due to the physiologic and extra-physiologic artifacts. There are several techniques are intended to manipulate the EEG recorded signal during the BCI preprocessing stage of to achieve preferable results at the learning stage. This paper aims to present an overview on BCI different EEG brain signal recording artifacts and the methodologies to remove these artifacts from the signal focusing on different novel trends at BCI research areas.

INTRODUCTION

The BCI research has arisen at the last decade. BCI research and development has focused primarily on neuro-prosthetics applications that aim to restore damaged hearing, sight and movement [1]. Nowadays, BCI research reached remarkable results at robot control [6, 8, 9, 12], motor disabilities recovery using BCI chip implants [1, 4, 5, 7, 11], medical diagnoses and prediction [15, 18], security and authentications [14] and game controlling [10, 16, 17]. Figure 1 illustrates different BCI research.

Brain cells communicate with each other through electrical impulses that structure the brain signal. There are several techniques for brain signal acquisition: invasive, semiinvasive, and non-invasive [10, 19]. EEG technique (which this paper concern) is a non-invasive technique for brain signal acquisition. It records brain signal along the scalp through measuring voltage fluctuations accompanying neurotransmission activity within the brain. The main advantages of EEG are that it is non-invasive so that there is no surgical intervention needed to set the electrodes on the brain, relative ease of use, portable, excellent time resolution (it gives the ability to see brain activity as it unfolds in real time, at the level of milliseconds (thousandths of a second)), low-cost comparing to the other brain signal acquisition techniques. The disadvantages of EEG that its very small signal to noise ratio and spatial localization resolution represent a limitation compared to other brain signal acquisition methods. According to the very small signal to noise at the EEG signal recorded, it cannot be directly used at processing stage such as feature extraction and pattern recognition directly at the BCI system. The EEG recorded signal has to pass through filtering and artifact removing at the preprocessing stage at BCI system. Figure 2 illustrates the BCI system stages and its components [20].