(Research Article) Integration of BCI and Eye Gaze Tracker to Control Mouse H. M. Mehta 1* , Prof. M. P. Patel 2 , Dr. C. H. Vithalani 3 1*,2 Department of Electronics & Communication Engineering, B. H. Gardi College of Engineering and Technology, Rajkot, Gujarat, INDIA 3 Department of Electronics & Communication Engineering, Government Engineering College, Rajkot, Gujarat, INDIA Abstract This paper represents how EEG based BCI module can be used with HCI devices for the physically disabled people to interact with the surrounding world. EEG is one of the imaging technology which records electrical activity spontaneously generated from the brain. Owing to the less accuracy of this cheaper and affordable BCI module, it cannot be used where many control signals are required to operate any device. In this paper, Neurosky’s Brainwave starter kit has been used as a BCI module which has a mono channel sensor to acquire the brain signals. To increase the ability of such BCI module, Eye Gaze Tracker (Human Computer Interface) has been attached with it. By merging these two techniques, windows software of mouse controller is developed using Python language and OpenCV as a third party module. This python program file can also be used in other operating systems such as Linux, OSX etc. This software can be extremely useful to ALS (Amyotrophic Lateral Sclerosis) patients, paralyzed people, who are lacking any kind of muscular movement to control any devices. Keywords: BCI (Brain Computer Interface), EEG (Electroencephalography), HCI (Human Computer Interface), Eye Gaze Tracker, Python, OpenCV. 1. Introduction In India, there are about 5 million physically disabled people who are suffering from various diseases or some are disabled by born. They are unable to communicate with the surrounding world so effectively that they often come under depression. So requirement of making devices for them has been emerged and various types of BCI devices have been invented for their comfort and there still a lot of research is remaining to be done to use it effectively and which should be affordable to everyone. The BCI devices are used to acquire the brain signals and to control any devices using them. When a person thinks about something, neurons get fired in his mind and accordingly patterns of these neural activities are generated and that is in the form of electrical signals. So it can be measured by electrodes either placed on the scalp or on the surface of cortex or inside the skull. Based on this, [1] classifies BCI devices are into three categories: 1) Invasive method, 2) Partially Invasive method, 3) Noninvasive method. Invasive devices are implanted inside the skull by a critical surgery in which a chip is put inside the cortex which consists of hundreds of electrodes to measure the brain signals. It can give very accurate result but due to surgery, scar tissue is formed which can degrade the signal quality. So this method causes pain to patients, implementation is costly and maintenance is also required. In Partially Invasive method, electrodes are implanted inside the skull but rest remains outside the brain. So the signal becomes weaker in comparison with the Invasive devices but less risk of forming scar tissue. [2] Shows that Non-invasive device measures the brain signals by putting electrodes over the scalp. There is no surgery required in this method of BCI. Though skull is about 7mm thick, distortion occurs in the brain signals and it degrades the signal quality. But for the few controlling operations, it is quite good to use and affordable. So there should be some research towards increasing the accuracy of Noninvasive BCI. In this work, EEG based Neurosky’s brainwave starter kit is used which is a noninvasive BCI. There are many applications of this device mentioned below. Wireless mind controlled robot is made using this module in [3] which acquires the EEG signals using single channel sensor placed on the forehead and the signal feature is extracted using the Discrete Wavelet Transform so that blink strength detection can be made very accurate and by using it, wireless robot can be controlled. Another application is depicted in [4] which demonstrate the vigilance level of the driver. Drowsiness is the major problem scene in the drivers who must stay alert for a long period of time while driving. So BCI causes * Corresponding Author: e-mail: hardikmmehta3@gmail.com ISSN 2320-7590  2018 Darshan Institute of Engg. & Tech., All rights reserved INTERNATIONAL JOURNAL OF DARSHAN INSTITUTE ON ENGINEERING RESEARCH AND EMERGING TECHNOLOGIES Vol. 7, No. 1, 2018 www.ijdieret.in IJDI-ERET