Research Repository

A Smart Home Control Prototype Using a P300-Based Brain–Computer Interface for Post-stroke Patients

Cortez, Sergio A and Flores, Christian and Andreu-Perez, Javier (2020) A Smart Home Control Prototype Using a P300-Based Brain–Computer Interface for Post-stroke Patients. In: Proceedings of the 5th Brazilian Technology Symposium, ? - ?.

[img] Text
P300_smart_home-1.pdf - Accepted Version
Restricted to Repository staff only until 16 December 2021.

Download (327kB) | Request a copy

Abstract

In this paper, we present and compare the accuracy of two types of classifiers to be used in a Brain–Computer Interface (BCI) based on the P300 waveforms of three post-stroke patients and six healthy subjects. Multilayer Perceptrons (MLPs) and Support Vector Machines (SVMs) were used for single-trial P300 discrimination in EEG signals recorded from 16 electrodes. The performance of each classifier was obtained using a five-fold cross-validation technique. The classification results reported a maximum accuracy of 91.79% and 89.68% for healthy and disabled subjects, respectively. This approach was compared with our previous work also focused on the P300 waveform classification.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings of the 5th Brazilian Technology Symposium Emerging Trends, Issues, and Challenges in the Brazilian Technology, Volume 2
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 25 Mar 2021 16:14
Last Modified: 25 Mar 2021 17:15
URI: http://repository.essex.ac.uk/id/eprint/30091

Actions (login required)

View Item View Item