The main problem faced by paralyzed persons is their movement. Quadriplegic disease, a serious disability, affects all four limbs and requires external assistance to perform their daily activities. The main objective of this project is to provide an automated system for these persons. The Abstract discusses the possibility of developing a wheelchair that can be controlled by using eye sight and flash. User-defined gestures are translated into the screen position using the optical sensor in MATLAB. The wheelchair recognizes the vision / blink of the eye and if it matches the gestures in memory, the motion control commands are generated by a microcontroller according to the encoding.
These commands drive the wheelchair engines.
The powered wheelchair is a mobility device persons with moderate / severe physical disabilities. Different types of wheel control interfaces have been developed control: like joystick or head control. These forms of the interface may not be available for everyone. Through the use of eye blink and mouth gesture, different form of wheelchair control is possible.
This paper presents the design, development, the medical impact of the eye controlled wheel chair. People with quadriplegia can not operate a wheelchair using a joystick. However, some people feel it is difficult to handle the wheelchair in their hands due to paralysis, aging or disability.
Wide range of supporting devices and modern the equipment has been developed to help improve quality of life. This technology is integrating for a disabled individual in society.
Because all people can not use traditional electric chair, there should be some communicate between the user and the wheelchair to control it.
It is very difficult for the disabled user to drive the wheelchair with their arms.
Some commonly used methods are listed below. Wheelchair-based wheelchair system, acoustic wheelchair , acoustic wheelchair system, finger and finger-based wheelchair, eye-based electronic wheelchair which uses MATLAB, an electronic chair motion based on eye movement Which uses berry berries
Face detection using the violajones algorithm:
We used the “CascadeObjectDetector” to detect eye-shaped objects based on their shape and size. The Viola Jones algorithm is used for itself. Continuous snapshots are taken from each frame 25 and points of extracted features are saved, ie capturing approximately one shot per second and processing them. Depending on the position of the feature points in the previous shot and the current shot, motion is detected and connected to the wheelchair set via the serial port.
The Viola-Jones algorithm is a sub-window check that can detect faces through a specific entry. The standard image processing method is to resize the input image to different sizes and then run the fixed size detector through these images. It turns out that this method takes a long time due to the calculation of images of different sizes. Unlike the standard approach of Viola Jones
Re-measure the detector instead of the input image and turn on the detector several times in the image at a different size each time. At first, one may suspect that both methods consume time on an equal footing, but Viola Jones has devised a wide-ranging revealing that requires the same number of calculations of any size.
If the webcam detects multiple faces, the program will stop because it is difficult to identify the actual input. The following figure is an example of detecting multiple faces or non-faces, it will appear that the face is not detected.
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