In a rapidly evolving world, inclusivity and accessibility are essential principles in a society that is continually changing and marked by technological breakthroughs. One critical domain where these principles are paramount is mobility for individuals with physical disabilities. With the developments of modern techniques, many distinct kinds of devices—including wheelchairs — are available to help with mobility. 

Researchers have designed a technologically intelligent wheelchair that can recognize voice, gesture, facial cues, lane, and gaze in a natural setting for individuals with mobility impairments. In a paper presented at the 2024 International Conference on Emerging Smart Computing and Informatics (ESCI), an automatic wheelchair using AI technology and deep learning algorithms is discussed. The device promotes overall well-being with health-tracking capabilities and communication support for those unable to speak. Empower Wheel Chair redefines accessibility, providing users with newfound freedom, convenience, and connection in their daily lives.

Creating the Empower Wheel Chair

The paper begins by providing background information and related research before covering the methodology of the proposed system, which encompasses an integrated approach to developing an innovative and accessible wheelchair system. The main processing unit of the suggested system is a Raspberry Pi, which gathers input from a camera. 

According to the researchers, critical responsibilities of the camera's visual data acquisition are face tracking, gesture recognition, and lane detection. The wheelchair relies heavily on computer vision techniques for real-time tracking and interaction, which contribute to the wheelchair's intelligent navigation and creates a user-centric design:

  • Gesture Recognition: Involves training machine learning models to identify and classify specific hand gestures the user performs. 
  • Face Tracking: Employs facial landmark detection and PID (Proportional-Integral-Derivative) control techniques to monitor the user's face and head movements. 
  • Lane Detection: Allows the wheelchair to follow predefined paths or lanes, enhancing navigation accuracy indoors or outdoors. 
  • Color Tracking: Involves the segmentation of specific colors within the camera's field of view, enabling the wheelchair to track and follow a user-defined colored object, providing an additional means of control or interaction.
  • Gaze Control: By analyzing the user's eye movements and gaze points, the wheelchair can respond to the user's visual cues. 
  • Voice Assistant and Voice Commands: This feature combines natural language processing (NLP) and speech recognition techniques. Users can interact with the wheelchair by issuing voice commands, enabling tasks such as booking doctor appointments, ordering medications, or making emergency calls.
  • Safety and Redundancy: In the event of unexpected circumstances or system errors, the wheelchair is designed to prioritize user safety by halting or taking corrective actions.

The integration of these elements guarantees a unified system, and comprehensive documentation makes the hardware configuration, software installation, and settings understandable. As noted by the authors, ongoing testing and discussion of future developments enhance the system's robustness and potential for future upgrades.

Block diagram of Suggested System


Next Steps

The researchers explore how advanced technology can pave the way for a more inclusive and equitable future, especially for those grappling with mobility challenges. Empower Wheel Chair is a single AI-based system envisioned as a transformative solution with substantial societal benefits and a profound leap into the future of mobility, communication, and healthcare support. 

The proposed system integrates cutting-edge technologies into a user-centric wheelchair system that improves accessibility and expands users' quality of life by providing intuitive control mechanisms. Future directions include refining existing features, exploring new assistive capabilities, and ensuring adaptability to individual user needs through user feedback.

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