Advances in Mechatronics by H. Martinez-Alfaro

By H. Martinez-Alfaro

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And finally gamma (22 – 30 Hz) consists of low amplitude & high frequency waves resulting from attention or sensory stimulation. Figure 1 shows the normal EEG signal of a relaxed patient. The signal consists of beta waves which lie in the frequency range of 13 to 22 Hz. Figure 2 shows EEG signal with eye closure and eye opening. The negative amplitude shows the eyelids closure and positive value shows the opening of eyelids. Fig. 1. Normal EEG signal when a person is relax. Fig. 2. Normal EEG signal with eye closure and eye opening.

Friction was then seen to depend not only on velocity but magnitude and rate of the external force. This resulted in a complete Artificial Intelligent Based Friction Modelling and Compensation in Motion Control System 47 model of static friction as shown in Figure 2(c). However, Stribeck (1902) observed a decreasing friction with increasing velocity at low velocity during the transition from stiction to kinetic friction and he proposed the concept of Stribeck friction shown in Figure 2(d). In order to overcome the jump discontinuity of the model at zero velocity, a modification was introduced (Karnopp, 1985) by replacing the jump with a line of finite slope as shown in Figure 2(e).

Conclusion A system that can activate a fan using EEG signal detected by a microcontroller has been described in this paper. The results showed that eye blinks can be detected successfully using PIC16F877A. With a program running on PIC16F877 microcontroller, a simple motor 42 Advances in Mechatronics can be activated using neural signal. This application is suitable for people who cannot move their hands or the whole body to control a fan. Using this system, users can control a fan easily without any conventional remote controller.

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