Design and implementation of a prototype of an electrooculographic signal processing system oriented to control - by wink - the instant messaging environment Telegram for users with motor limitations in upper limbs

This paper is based upon the design and implementation of a Human Computer Interface (HCI) as a support tool for people with upper limb disabilities, especially those with difficulties in speech, so as to interact and communicate by Instant Messaging Environments (IME). For this, we have implemented the appropriate hardware for acquisition and conditioning of the electrooculografic signal. As for the software, we have developed a wink pattern recognition algorithm composed of three processes: zero crossing technique adapted to the level of direct current (DC), comparison of the energy threshold and the Pearson correlation coefficient. Besides, a virtual keyboard was implemented to allow users to select, by means of winks, the characters that they wanted to transmit messages by the IME Telegram. Finally, the system was tested by potential users obtaining a success rate of 94.90% that proof how effective and reliable it is.