The thesis focuses on the development of a system that combines electroencephalography (EEG) with an actuator – a robotic arm. EEG is a method of measuring brain activity via electrodes and is often used in the field of brain-computer interaction.
In addition to assembling and controlling the robotic arm, the project also involved the transfer of data between the EEG measuring device and the actuator, as well as the analysis of EEG signals. We designed the system so that the robotic arm clenches into a fist when the user is highly focused and relaxes into an open palm when the attention is low.
The results demonstrate a functioning system that uses EEG signal to control a mechanical arm. The system is useful for further research in the fields of prosthetics and brain-computer interaction. A potential improvement in system accuracy involves reducing the noise caused by the sensitivity of EEG signals to muscle activity.
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