Brain Wave Controller for Stress Removal and Automation of Automobile Ignition to Prevent Driving Under Influence [Controlling Brainwaves Using Embedded Systems]

K KABILAN¹

¹DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING, NANDHA COLLEGE OF TECHNOLOGY, ERODE

Abstract

Stress is a prevalent and costly problem in today's workplace. It is the harmful physical and emotional response that occurs when there is a poor match between job demands and the capabilities, resources, or needs of the worker. Persistence of stress results in cardiovascular disease such as depression, concentration and memory loss. Addiction is one of the chronic disorders that are characterized by the repeated use of substances or behaviors despite clear evidence of morbidity secondary to such use. It is a combination of genetic, biological / pharmacological and social factors. Example: gambling, alcohol drinking, taking narcotic drugs and certain mannerisms. The therapies at present consume time. About 24% of the accidents taking place are due to drunken drive. A driver subjected to long drive falls sleepy and ends up in accident. In this paper we briefly discuss about the brain wave and brains reaction during stress, addiction and drunk. This paper also explains you the basic task of Brainwave Controller, that how stress, addiction is identified with the help of brainwave and how these are controlled using the principle binaural beats. Also we have designed a device to detect the brainwaves and process it to determine whether it is addiction or stress. In addition to controlling of brainwaves, it also has a feature to avoid an individual who consumes alcohol to drive a vehicle. This paper promises to be an economical solution for the people who suffer from stress, addiction and to prevent accidents.

Keywords

• Brain Wave Controller, Stress Removal, Automobile Ignition

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Cite this Article as Follows

K KABILAN. "Brain Wave Controller for Stress Removal and Automation of Automobile Ignition to Prevent Driving Under Influence [Controlling Brainwaves Using Embedded Systems]." International Conference on Information Engineering, Management and Security (2015): 74-80. Print.