Hand Gesture using for Impaired People in Open CV
The project introduces a movement and gesture recognition communication system that converts hand gestures into meaningful communication, with the aim of assisting people with communication challenges. Leveraging the hand-tracking capabilities of MediaPipe and video processing capacity of OpenCV, the system is made to operate on the Raspberry Pi platform. It identifies certain hand gestures and translates them into predetermined messages based on basic needs such as food, water, or assistance. These gestures are then translated into speech using a text-to-speech engine, allowing users to communicate effectively. The system not only allows regular communication but also has an emergency feature, which enables users to call for immediate assistance. With the integration of advanced computer vision and low-cost hardware, the system improves accessibility for users of varying financial backgrounds. This pioneering approach illustrates how assistive technology can enhance personal freedom, security, and quality of life, empowering individuals experiencing difficulties in oral communication. The design of the system prioritizes simplicity and affordability, opening up the possibility of more inclusive and specialized devices with a profound effect on users' lives.
Authors
- Santhosh Kumar G
- K. Gowtham
- G Rajarathnam
- R Dharanidhar
- J Sachinkumar
Institutions
- Karpagam Academy of Higher Education (IN)
Publication Details
- Published
- 2025-03-19
- DOI
- https://doi.org/10.1109/iciccs65191.2025.10985489
- Primary Topic
- Stroke Rehabilitation and Recovery
- Type
- article
- Field-Weighted Citation Impact
- 0.00