Steady–state visually evoked EEG signal processing with tuneable continuous–time bandpass sigma–delta modulators

We present a non-invasive brain-machine-interface (BMI) prototype system which allows the simple control of a switch. The main goal of the system, based on electroencephalogram (EEG) recordings, is to create mechanical action from brain activity. Experimental work presented in this paper outlines the operation of a system which is based on a tuneable continuous-time bandpass SigmaDelta modulator used to detect the frequency signature of SSVEP waveforms. Simple time-frequency-space domain signal analysis methods are employed to generate the electrical control-signal, sufficient to control a robotic motion. Our simulation demonstrated around 90% success rate in decoding SSVEP activity.