The International Conference on Automation, Cognitive Science, Optic, Micro-Electro Mechanical System, and Information Technology, ICACOMIT 2015, Bandung - Indonesia, 28 - 30 October 2015

Senin, 08 Mei 2017 10:16 | Sudah dibaca 1162 kali

In this paper, an application of Adaptive Network Fuzzy Interference System on EEG-SSVEP classification for brain-controlled wheelchair is presented. The used of steady-state paradigms with a periodic visual stimulus to stimulate the EEG-SSVEP is focused. In the experiment, four subjects with age about 25±1 years were tested. The experimental results show that the implementation of the proposed method achieves a great statistical improvement in classifying peak amplitude features with greater than 90% accuracy.

Tautan ke artikel di IEEE Xplore Digital Library

Kata Kunci: Neural Networks; ANFIS; Feature extraction; Classification; EEG-SSVEP; BCI