Microprocessor based algorithms for controlling Electromyogram-driven devices

The purpose of this study was to develop and evaluate signal-processing algorithms for controlling devices with electromyogram (EMG). An “EMG-driven car model” was developed whereby a remote control toy car was navigated by using two-channel EMG signals recorded from the right and left forearms with surface electrodes. After the EMG signals were amplified and filtered, they were digitized and processed with a PIC18F452 microprocessor. Two threshold detection algorithms with and with an infinite impulse response (IIR) filter were compared. The detected signals were used to navigate the car via a radio-frequency transmitter. This microprocessor-based system is useful for developing EMG-driven assistive technology devices.