TY - GEN
T1 - A Cloud-based Brain-controlled Wheelchair with Autonomous Indoor Navigation System
AU - Lakas, Abderrahmane
AU - Kharbash, Fekri
AU - Belkacem, Abdelkader Nasreddine
N1 - Funding Information:
The authors would like to thank Mohamed Lakas, (student at Abu Dhabi University), for his participation in the BCI experiments. This project was supported in part by Emirates Center for Mobility Research project number: G00003500, and UAE University's National Space Science and Technology Center Project number G00003280.
Funding Information:
ACKNOWLEDGMENT The authors would like to thank Mohamed Lakas, (student at Abu Dhabi University), for his participation in the BCI experiments. This project was supported in part by Emirates Center for Mobility Research project number: G00003500, and UAE University’s National Space Science and Technology Center Project number G00003280.
Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Paralysis is the most inhibiting among all the severe motor disabilities. Indeed, people are inflicted with paralysis as the result of an accident or a medical condition that affects - completely or partially, the way muscles and nerves function. However, these patients are cognitively aware, and their mental abilities are unimpaired, and can still be autonomous and more useful in many other ways than many able-bodied people. Brain-computer interface (BCI) technology is now being incorporated into the treatment of physically impaired patients offering them an improved mobility and thus autonomy. In this paper, we propose to develop a smart brain-controlled wheelchair with autonomous navigation system for people with severely impaired motor functions. Our proposed solution allows its users to move around in indoor premises with great flexibility and minimum instructions. That is, high-level commands such as”Go to location X” is enough for the wheelchair to move to the desired location while finding its way around obstacles and obstructions. This system relies on two main components: a BCI interface to issue high level commands to the wheelchair, and a component for autonomous indoor navigation system which integrates all the elements of path planning obstacle detection and avoidance. In addition, the solution relies on the use of trained models that are deployed in cloud and provided as facility specific services.
AB - Paralysis is the most inhibiting among all the severe motor disabilities. Indeed, people are inflicted with paralysis as the result of an accident or a medical condition that affects - completely or partially, the way muscles and nerves function. However, these patients are cognitively aware, and their mental abilities are unimpaired, and can still be autonomous and more useful in many other ways than many able-bodied people. Brain-computer interface (BCI) technology is now being incorporated into the treatment of physically impaired patients offering them an improved mobility and thus autonomy. In this paper, we propose to develop a smart brain-controlled wheelchair with autonomous navigation system for people with severely impaired motor functions. Our proposed solution allows its users to move around in indoor premises with great flexibility and minimum instructions. That is, high-level commands such as”Go to location X” is enough for the wheelchair to move to the desired location while finding its way around obstacles and obstructions. This system relies on two main components: a BCI interface to issue high level commands to the wheelchair, and a component for autonomous indoor navigation system which integrates all the elements of path planning obstacle detection and avoidance. In addition, the solution relies on the use of trained models that are deployed in cloud and provided as facility specific services.
KW - Autonomous systems
KW - Brain Computer Interface (BCI)
KW - Electroencephalography (EEG)
KW - P300-based wheelchair Control
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U2 - 10.1109/IWCMC51323.2021.9498751
DO - 10.1109/IWCMC51323.2021.9498751
M3 - Conference contribution
AN - SCOPUS:85125666767
T3 - 2021 International Wireless Communications and Mobile Computing, IWCMC 2021
SP - 1727
EP - 1733
BT - 2021 International Wireless Communications and Mobile Computing, IWCMC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Wireless Communications and Mobile Computing, IWCMC 2021
Y2 - 28 June 2021 through 2 July 2021
ER -