Open Architecture for the Control of a Neuroprosthesis by Means of a Mobile Device

The Brain-Computer Interfaces (BCI) based on Electroencephalography (EEG), allow that through the processing of impulses or electrical signals generated by the human brain, people who have some type of severe motor disability or suffer from neurological conditions or neurodegenerative diseases, can establish communication with electronic devices. This paper proposes the development of an expert system that generates the control sequences for a neuroprosthesis that will be used in the rehabilitation of patients who cannot control their own muscles through neuronal pathways. This proposal is based on the EGG record during the operation of a BCI under the rare event paradigm and the presence or not of the P300 wave of the Event-Related Potential (ERP). Feature extraction and classification will be implemented on a mobile device using Python as a platform. The processing of the EEG records will allow obtaining the information so that an Expert System implemented in the mobile device, is responsible for determining the control sequences that will be executed by a neuroprosthesis. The tests will be performed by controlling a neuroprosthesis developed by the Instituto Nacional de Rehabilitación in México, which aims to stimulate the movement of a person’s upper limb.