Memorias de investigación
Communications at congresses:
Linear vs Nonlinear Classification of Social Joint Attention in Autism Using VR P300-Based Brain Computer Interfaces
Year:2019
Research Areas
  • Electronic technology and of the communications
Information
Abstract
VR P300-based BCI has proven to be a suitable method for training social attention skills in youngsters with autism spectrum disorder (ASD). In this study, we present a method that could be used in such an application to identify which object the user is paying attention to in a virtual environment by means of EEG recordings only. Temporal and time-frequency features were explored. Furthermore, the prediction accuracy of linear and nonlinear classification methods was assessed and compared, along with their computational times and complexity, and linear discriminant analysis (LDA) yielded the best overall performance (82%). The successful predictions and low computational times demonstrate the feasibility of the proposed solution for a VR-BCI neurorehabilitation tool.
International
Si
Congress
XV Mediterranean Conference on Medical and Biological Engineering and Computing ? MEDICON 2019
960
Place
Coimbra, Portugal
Reviewers
Si
ISBN/ISSN
978-3-030-31635-8
10.1007/978-3-030-31635-8
Start Date
26/09/2019
End Date
28/09/2019
From page
5
To page
11
Proceedings of MEDICON 2019, September 26-28, 2019, Coimbra, Portugal
Participants
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Bioingeniería y Telemedicina
  • Departamento: Tecnología Fotónica y Bioingeniería
  • Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB