In the last years, the manufactured vehicles were designed to focus on prevention of some risky situations caused by a human driver. The aim of this paper is to illustrate the design and implementation of a BCI system which can detect the arm movements by the EEG signal during a simulated driving session. The proposed approach to realize a classifier able to recognize the arm movement by EEG feature analysis is based on the consecutive application of a Time Delay Neural Network (TDNN) and a Pattern Recognition Neural Network (PRNN). Preliminary tests are shown on three different participants between 24 and 45 years old.

A BCI driving system to understand brain signals related to steering

Zero E.;Graffione S.;Bersani C.;Sacile R.
2021

Abstract

In the last years, the manufactured vehicles were designed to focus on prevention of some risky situations caused by a human driver. The aim of this paper is to illustrate the design and implementation of a BCI system which can detect the arm movements by the EEG signal during a simulated driving session. The proposed approach to realize a classifier able to recognize the arm movement by EEG feature analysis is based on the consecutive application of a Time Delay Neural Network (TDNN) and a Pattern Recognition Neural Network (PRNN). Preliminary tests are shown on three different participants between 24 and 45 years old.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1078328
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