Home Automation Using EEG Signals

Harish Verlekar

Abstract


We propose to use EEG Signals for Home automation. Home automation can be totally revolutionized using EEG Signals and computer. Brain produces various types of waves like alpha (9-13Hz), beta (14-30Hz), theta (4- 8Hz), delta (1-3Hz).Using these waves we can control various home appliances. The entire concept consists of 4 main stages detection, amplification, processing, output. First detecting the brain signals using an EEG cap or electrodes. These brain signals are very weak hence in second stage we need to amplify these brain signals to a usable amount and filter these to remove noise. Then thirdly, we will have to convert these signals into digital by using A to D converter and into a type a computer software or a microcontroller can understand. Fourth, taking this decoded signal and sending these signals wirelessly, by using an RF circuit to a distant switch circuit, which will turn on or off the appliance in vicinity. Using this technology the life of people would be further simplified, physical efforts would be considerably reduced and it would also prove as a boon for physically disabled people.


Keywords


EEG(Electroencephalographic), Automation

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References


S. G. Mason, M. M. Moore Jackson, and G. E. Birch, “A general framework for characterizing studies of brain interface technology,” in Annuls of Biomedical Engineering, vol. 33, no II, pp 1653-1670, Nov. 2005. [2] C. Guger, A. Schlögl, C. Neuper, D. Walterspacher, T. Strein, and G. Pfurtscheller, “Rapid prototyping of an EEG-based braincomputer interface (BCI),” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 9, no. 1, pp. 49– 58, March 2001. [3] T. M. Vaughan, J. R. Wolpaw, and E. Donchin, “EEGbased communication: Prospects and problems,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 4, no. 4, pp. 425–430, Dec 1996. [4] K. R. Müller and B. Blankertz, “Toward non-invasive braincomputer interfaces,” IEEE Signal Processing Magazine, vol. 128, no. 1, pp. 125-128, 2006. [5] J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, “Brain-computer Interface for Communication and Control,” Clinical Neurophysiology, vol. 133, pp. 767-791, 2002. [6] Benbadis, Selim, et al. “Handbook of EEG Interpretation.” Demos Medical, 2007. [7] S. Helal, W. Mann, H. E. Zabadani, J. King, Y. Kaddoura, and E. Jansen, “The gator tech smart house: A programmable pervasive space,” IEEE Comput. Soc., vol. 38, pp. 50-60, 2005


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