An intelligent wheelchair based on automated navigation and BCI techniques

Area of Science:

• Biomedical Engineering
• Robotics
• Human-Computer Interaction

Background:

• Intelligent wheelchairs aim to enhance mobility for individuals with disabilities.
• Existing systems often require significant user cognitive load for control.
• Adaptive navigation is crucial for safe and efficient wheelchair operation in dynamic environments.

Purpose of the Study:

• To develop and evaluate an intelligent wheelchair system integrating a brain-computer interface (BCI) with automatic navigation.
• To reduce the mental burden on users by automating destination selection and path planning.
• To create a system capable of adapting to environmental changes during navigation.

Main Methods:

• A P300-based brain-computer interface (BCI) was employed for user destination selection.
• Automatic generation of candidate destinations and waypoints based on environmental sensing.
• Integration of a path planning algorithm for autonomous wheelchair navigation.
• Implementation of a BCI-controlled stop command for user intervention during motion.

Main Results:

• The intelligent wheelchair system successfully navigated to user-selected destinations.
• The P300-based BCI enabled intuitive destination selection with reduced cognitive load.
• The system demonstrated adaptability to environmental changes during operation.
• Experimental results confirmed the system's effectiveness and user-friendliness.

Conclusions:

• The proposed intelligent wheelchair system effectively combines BCI and automatic navigation.
• The system significantly alleviates the mental burden for users requiring mobility assistance.
• The adaptive navigation capabilities enhance the safety and usability of intelligent wheelchairs.