IRIS Recognition-Based Wheelchair for Quadriplegia Prone Persons

Anchal and Priyanka Bansal

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2023, vol. 9, issue 9, 169-171

Abstract: This abstract presents the concept of an iris recognition-based wheelchair system designed specifically for individuals with quadriplegia, a condition that results in paralysis of all four limbs. The proposed wheelchair aims to enhance the mobility and independence of quadriplegia-prone individuals by utilizing iris recognition technology to facilitate seamless control of the wheelchair's movement. The system utilizes a non-intrusive iris recognition algorithm to accurately identify the user's iris patterns, which are unique to each individual. By integrating this technology into the wheelchair's control system, the user can navigate the wheelchair by simply focusing their gaze on specific directions or objects within their field of vision. The system captures real-time iris images and processes them using advanced computer vision techniques to determine the intended movement commands. Through this innovative approach, the wheelchair eliminates the need for physical contact or manual input devices, thereby offering a more natural and intuitive control mechanism for individuals with quadriplegia. The iris recognition-based control system not only enables precise navigation but also provides customizable features such as speed adjustment, obstacle detection, and path planning, ensuring a safe and efficient user experience. Furthermore, the proposed system incorporates machine learning algorithms to continuously improve the iris recognition accuracy and adapt to individual users' changing eye patterns over time. This adaptive learning capability enhances the system's reliability and ensures consistent and reliable control of the wheelchair.

Keywords: Quadriplegia; Wheelchair; Adaptive Learning; Iris (search for similar items in EconPapers)
Date: 2023
Note: Article URL: https://ijsrcseit.com/CSEIT239922
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrcseit.com/CSEIT239922 Article URL (text/html)
https://ijsrcseit.com/paper/CSEIT239922.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v9:y2023:i9:id:hcseit239922

DOI: 10.32628/CSEIT239922

Access Statistics for this article

More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma (USA) ().