Research Article
Robotic Control by EOG-EEG-RFID based Multimodal Interface and Shared Control Technology
@INPROCEEDINGS{10.4108/eai.16-4-2022.2318075, author={Preeti Kumari and Lini Mathew and Neelesh Kumar}, title={ Robotic Control by EOG-EEG-RFID based Multimodal Interface and Shared Control Technology}, proceedings={Proceedings of The International Conference on Emerging Trends in Artificial Intelligence and Smart Systems, THEETAS 2022, 16-17 April 2022, Jabalpur, India}, publisher={EAI}, proceedings_a={THEETAS}, year={2022}, month={6}, keywords={ssvep eog multimodal robot control eeg rfid shared control mmi}, doi={10.4108/eai.16-4-2022.2318075} }- Preeti Kumari
Lini Mathew
Neelesh Kumar
Year: 2022
Robotic Control by EOG-EEG-RFID based Multimodal Interface and Shared Control Technology
THEETAS
EAI
DOI: 10.4108/eai.16-4-2022.2318075
Abstract
This study describes a robotic control application that uses Radio Frequency Identification (RFID) technology as shared control architecture and Electrooculography (EOG) and Electroencephalography (EEG) biosignals for multimodal Man-Machine Interface. The proposed application had to steer a robot along a given route aimed at helping people with mobility disabilities in performing daily tasks independently. With proper threshold selection, EOG signals were classified. Whereas, EEG interface used Minimum Energy (ME) combination for feature extraction and Linear Discriminant Analysis (LDA) based classifier. Both EOG and EEG signals had been synchronously used for robotic movement control and both complements each other. Further, RFID was used to identify the object and perform the pick/place operation. The proposed model provides longer range of applications with less fatigue. The effectiveness of the proposed model had been verified by controlling a mobile robot successfully.