The use of electroencephalogram (EEG) waves in the field of Brain Computer Interfaces (BCI) has recently attracted a lot of interest, with varied applications ranging from entertainment to medicine emerging, showing that EEG waves are suitable for controlling appliances through a microcontroller. This study presents an offline strategy for the extraction of digital control signals from brain EEG waves using MATLAB/SIMULINK. The principle is applied as follows: (i) the extraction of α- and β-bands from the original brain EEG wave; (ii) detection of the peaks of both bands; and (iii) calculation of the power density of both bands to classify the mental mode and to generate appropriate control signals. Simulation results including signal processing tracking for various EEG waves are demonstrated that verify the effectiveness of the proposed strategy in terms of using brain EEG waves for apparatus control.
Electrosurgical generators (ESGs) are currently the most widely used surgical technology for clinical operations. The main disadvantage of ESGs is their output power is irregular due to the variable tissue impedance. The heat dissipation caused by the high amount of thermal energy generated leads to medical complications for both patient and surgeon. In this research, various inverter topologies and power controllers are investigated to specify the best structure that ensures best performance. The type of inverter topologies investigated are three level and five level, while the PID structures investigated are integer order (IO-PID) and fractional order (FO-PID). The simulation results indicate that FO-PID with five level inverters is better than IO-PID with three level inverters in terms of minimum heat dissipation rate and THD of the output voltage and current.
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