Title :
Brain-machine interface based on EEG mapping to control an assistive robotic arm
Author :
Úbeda, Andrés ; Azorín, José M. ; García, Nicolás ; Sabater, José M. ; Pérez, Carlos
Author_Institution :
Virtual Reality & Robot. Lab., Univ. Miguel Hernandez, Elche, Spain
Abstract :
In this paper, a non-invasive spontaneous brain-machine interface (BMI) based on the correlation of EEG maps has been used to control 2D movements of an assistive pneumatic planar robot. The main goal of the system is to assist disabled people in pick and place tasks. The BMI has been tested in order to check the accuracy of the system. To that end, several planar movements between different positions have been performed. The control of the 2D movement is performed by using a hierarchical control where the user has to first choose the axis and then decide the movement direction. All the commands are generated using the spontaneous BMI. The results obtained show a very high reliability on the positioning and indicate that this control can be very useful in future assistive applications for disabled users. Further research will be centered in performing pick and place operations with daily objects using a pneumatic gripper attached at the end effector of the planar robot.
Keywords :
brain-computer interfaces; electroencephalography; end effectors; grippers; handicapped aids; medical robotics; position control; 2D movements control; BMI; EEG mapping; assistive pneumatic planar robot; assistive robotic arm control; command generation; disabled people assistance; end effector; hierarchical control; movement direction; noninvasive spontaneous brain-machine interface; pick-and-place tasks; pneumatic gripper; positioning; Brain models; Correlation; Electrodes; Electroencephalography; Pneumatic systems; Robots;
Conference_Titel :
Biomedical Robotics and Biomechatronics (BioRob), 2012 4th IEEE RAS & EMBS International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4577-1199-2
DOI :
10.1109/BioRob.2012.6290689