TY - GEN
T1 - Open Architecture for the Control of a Neuroprosthesis by Means of a Mobile Device
AU - Contreras-Martínez, Adrián
AU - Carvajal-Gámez, Blanca E.
AU - Rosas-Trigueros, J. Luis
AU - Gutiérrez-Martínez, Josefina
AU - Mercado-Gutiérrez, Jorge A.
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Brain-Computer Interface
KW - EEG
KW - Mobile devices
KW - Motor imagination
KW - Neuroprosthesis
UR - http://www.scopus.com/inward/record.url?scp=85097228332&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-60703-6_4
DO - 10.1007/978-3-030-60703-6_4
M3 - Contribución a la conferencia
AN - SCOPUS:85097228332
SN - 9783030607029
T3 - Communications in Computer and Information Science
SP - 25
EP - 31
BT - HCI International 2020 – Late Breaking Posters - 22nd International Conference, HCII 2020, Proceedings
A2 - Stephanidis, Constantine
A2 - Antona, Margherita
A2 - Ntoa, Stavroula
PB - Springer Science and Business Media Deutschland GmbH
T2 - 22nd International Conference on Human-Computer Interaction, HCI International 2020
Y2 - 19 July 2020 through 24 July 2020
ER -
