Combining biosignals with RFID to develop a multimodal-shared control interface

Abstract

Abstract The paper presents an approach to develop assistive devices by combining multimodal biosignals and radio frequency identification (RFID). The brain and eye signals have been used as multimodal biosignals to control the movement of a robot in four directions and help reach near the object following a predefined path. RFID shared control over object identification, and the gripper arm connected at the end effector of the robot performs pick and place operations. Horizontal electrooculography (EOG) has been used for x-directional movement control and electroencephalography (EEG) signal obtained by visual stimulus, called steady-state visual-evoked potential (SSVEP) has been used for y-directional movement control of a robot. The SSVEP signal has also been used to ring an alarm in case of an emergency call by the user. Two parameters classification accuracy (CA) and information transfer rate (ITR) have been calculated for the performance evaluation of the proposed multimodal-shared control model and have shown improved results as compared to previous literature. The results also proved that the proposed model can be used for real-time mobility assistive applications.

Keywords

• EEG
• Shared control interface
• EOG
• MMI
• Robot control
• RFID technology