A multimodal wheelchair control system based on EEG signals and Eye tracking fusion

被引：0
|
作者：
Ben Taher, Fatma [1 ]
Ben Amor, Nader [1 ]
Jallouli, Mohamed [1 ]
机构：
[1] Univrsit Sfax, Ecole Natl Ingnieurs Sfax, Sfax, Tunisia
来源：
2015 INTERNATIONAL SYMPOSIUM ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA) PROCEEDINGS | 2015年
关键词：
data fusion; EEG signal; eye tracking; multimodal system control and threshold adaptation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Controlling an electric powered wheelchair (EPW) is not always a simple task for certain types of disabled person. For example, persons suffering from the locked in syndrome or ALS. Many researchers use the eye tracking or the brain signals as alternative ways to control the EPW. The goal of this paper is to illustrate the EPW control performance amelioration when using multi sources compared to single source control. The first part is to elaborate separate control techniques using ElectroEncephalography (EEG) then eye tracking technologies. The second part, is combining these techniques using data fusion algorithms. Finally, testing the control performance with EEG, Eye tracking and EEG/Eye tracking.
引用
收藏
页码：254 / 261
页数：8
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