IoT based Eye Movement Guided Wheelchair driving control using AD8232 ECG Sensor 
Pratik Kanani1, Mamta Padole2
1Pratik Kanani, Assistant Professor, Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, University of Mumbai, India.
2Dr. Mamta Padole, Associate Professor, Department of Computer Science and Engineering, The Maharaja Sayajirao University of Baroda, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5013-5017 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8182118419/2019©BEIESP | DOI: 10.35940/ijrte.D8182.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Each and every muscular movement in the body is induced by electrical signals. These electrical signals are in mV and they are very sensitive to noise factors like electrical gadgets placed nearby, different movements, earthing, etc. If such signals are traced carefully, they can be used to accomplish multiple tasks. Such signals are called Myographs. This paper proposes a new method for eye-movement tracking, using Arduino Nano along with AD8232, i.e. the ECG Sensor. Most of the devices for Eye Tracking need to be placed right on the eye which sometimes use Infrared Radiations which may be harmful to eyes. This proposed method captures the gaze direction by muscular contraction, also called Myography. This is done by placing the electrode pads on the forehead and the ECG line graphs demonstrate the direction of gaze which can be understood using the convolution method. After the movement direction is decided based on convolution method, the values are sent and received from the IoT cloud. Thus, the wheelchair movement can be controlled by online and offline modes, making it more opportune to the patient. The goal of the system is to avail low-cost solutions to the needer.
Keywords: AD8232, Arduino Nano, Convolution, ECG, Eye Tracking, Myography, Saccades.
Scope of the Article: Robotics and Control.