Abstract
The desire to be able to control things with merely thinking about it has existed for a long time. This could be as simple as changing the channel on the television to concepts as advanced as driving a car. Increased research in this field has caused a gap in technology and cost. Low-cost items that are regarded as toys do not provide sufficient neural activity signals to be processed while clinical systems with large number of high quality signals are cost prohibitive. In this project, a system is laid out that is both reasonable in cost as well as can provide neural signals to a computer that has high enough fidelity to be classified as different mental activity. An overview of the neuron to scalp electrical characteristics is examined. As well, the identification of low-cost electrodes and placement of the electrodes is performed. An amplification and filtering circuit card assembly is developed along with identifying an existing analog-to-digital conversion circuit card assembly to be used in this task. A small digital signal processing algorithm is developed to analyze and classify the detected signals. This project provides a good starting point for further work that needs a mid-level electrocardiogram for signal analysis.