Eye movement detection for wheelchair control application

IAEME PUBLICATION, 2020

According to the latest report prepared by the World Health Organization and the World Bank, 15 percent of the world's population is disabled [2]. The use of power-driven wheelchairs with high navigational intelligence is a great step to integrate severely handicapped and mentally ill people. Different systems are being developed, allowing the end-user to perform safe movements and accomplish some daily life important tasks [4]. The notion is to create an Eye Monitored System that allows wheelchair navigation depending on the movement of the eyes. We have built a device where a patient sits in a Wheel Chair looking directly at the camera; can move in a direction just by looking in that direction. Our Robotic wheelchair uses the image processing system to control the wheelchair. The user's eye movements are turned to a screen position using a camera, without any direct contact. In addition, we can give more independence to the disabled person to communicate with the devices in a room, for example: a light, a fan. This communication is done using a MEMS Accelerometer. Using this, the person can handle various devices easily.

international journal for research in applied science and engineering technology ijraset, 2020

The Eye Directive wheelchair may be a mobility-monitored device for persons with moderate/severe physical disabilities or chronic diseases also as for the elderly. There are various interfaces for wheelchair available within the market, still they continue to be under-utilized, the rationale being the power, power and mind presence required to work them. The proposed model is a possible alternative. In this model, we use the optical-type eye tracking system to control powered wheelchair. User's eye movements are translated to screen position using the optical type eye tracking system, with none direct contact. When user looks at convenient angle, then computer input system will send command to the software supported the angle of rotation of pupil i.e., when user moves his eyes balls left (move left), right (move right), straight (move forward) altogether other cases wheel chair will stop. Also, obstacle detection sensors are connected to the Arduino to supply necessary feedback for correct operation of the wheelchair and to make sure the user's safety. The motors appended to the wheelchair support differential steering which avoids clumsy motion.

International Journal of Advanced Computer Science and Applications

The inability to control the limbs is the main reason that affects the daily activities of the disabled which causes social restrictions and isolation. More studies were performed to help disabilities for easy communication with the outside world and others. Various techniques are designed to help the disabled in carrying out daily activities easily. Among these technologies is the Smart Wheelchair. This research aims to develop a smart eye-controlled wheelchair whose movement depends on eye movement tracking. The proposed Wheelchair is simple in design and easy to use with low cost compared with previous Wheelchairs. The eye movement was detected through a camera fixed on the chair. The user's gaze direction is obtained from the captured image after some processing and analysis. The order is sent to the Arduino Uno board which controls the wheelchair movement. The Wheelchair performance was checked using different volunteers and its accuracy reached 94.4% with a very short response time compared with the other existing chairs.

International Journal of Intelligent Engineering and Systems

People with deficiency hands and feet, especially people with multiple disabilities has difficulty for navigation. Therefore, this research proposed an approach to help them using an electric wheelchair and control it using their eyeball movements. However, eyeball movement detection is still a problem due to the lack of standardized methods such as low accuracy for several gazes especially for downward and forward movements that caused by failure tracking mechanisms. Failure tracking mechanism mostly caused by failure pupil detection and tracking processes. According to the conducted research, there is a relation between eyeball movement and eyelid movement. Due to the relation, it can be concluded that the movement of the eyeball can be detected by utilize the eyelid movement without using the tracking mechanism. Hence, in this research, we propose an approach to detect the five movements of the eyeball using Eye-mark based on contour and edge detection. Our proposed method produces a brisk result with 91,2% of accuracy and better computational time compared with other marking methods. Accordingly, it is interesting on how to relate between eyeball movements and electric wheelchair navigation mechanism.

2018

People suffering from quadriplegia are unable to use both their hands and their legs. In such a scenario, they are dependent on others to move them around which results in a loss in their self-confidence. The only movements they are able to achieve are their heads and therefore their eyes. This paper leverages this movement of the eye and implements a method to track the movement of the eye to automatically control a wheelchair. A vision based system is utilized here, wherein the web-camera of the laptop is utilized to acquire images of the patient. By implementing the Viola Jones algorithm, the eyes of the patient are detected. Using MATLAB, these images undergo various morphological processes and on further analysis eye movements are tracked to determine in which direction the wheelchair is to be moved. These signals are then sent to the Arduino which forwards it on to the DC motors via the L293D IC.

2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC), 2023

This article proposes a system that aids people with disabilities. An Electric Eye Controlled Wheelchair System is built to help disabled people. With the designed system, disabled people can move effortlessly without support from others. The system uses image acquisition wherein the image of the eye is processed to find out the gaze direction of the eye using Haar cascade and gaze estimation algorithms and hence wheelchair moves according to the direction of eyeball movement. The gaze estimation algorithm is so precise and one single algorithm does the job of what two algorithms (Canny Edge detection, Hough Transform) are supposed to do and to execute the same task. With this technique, a disabled person can steer their wheelchair with their eye movement. The webcam is placed in Infront of the person which captures the live movements, and an image processing technique is used to track the position of the pupil in both eyes with the help of a raspberry pi processor. The image processing technique used here is Gaze tracking which uses Open CV. The gaze tracking tracks pupil movement and depicts its coordinates. According to pupil motion, the motor driver will be instructed to go forward, left, and right. A blink instruction is used to stop the wheelchair when the person blinks. Additionally, a front-mounted ultrasonic sensor that can detect obstructions and automatically halt wheelchair movement is mounted for safety reasons. The system is monitored by a Raspberry Pi device, which lowers the cost.

In this paper, we use the optical-type eye tracking system to control powered wheelchair. The userís eye movements are translated to screen position using the optical-type eye tracking system. The pupil-tracking goggles with a video CCD camera and a frame grabber analyzes a series of human pupil images when the user is gazing at the screen. A new calibration algorithm is then used to determine the direction of the eye gaze in real time. We design an interface with nine command zones to control powered wheelchair. The command at the calculated position of the gazed screen is then sent to move the powered wheelchair.

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2015

This paper delivers a method to guide and control the wheelchair for disabled people based on movement of eye. This concept can be used for people with loco-motor disabilities. The proposed system involves three stages: image detection, image processing and sending of control signals wheelchair. The eye movement is detected using a head mounted camera. The images of the eye will be sent to the laptop where the images will be processed using Python software. The corresponding output signals are then send to the motor driving circuit which control the motors.

2018

This project presents the ‘eyeball Motion Controlled Wheelchair using IR Sensors for the elderly and differently abled people. In this eye tracking-based technology, two Proximity Infrared (IR) sensor modules are mounted on an eye frame to trace the movement of the iris. Since, IR sensors detect only white objects; a unique sequence of digital bits is generated corresponding to each eye movement. These signals are then processed via a micro controller IC (AVR328) to control the motors of the wheelchair. The potential and efficiency of previously developed rehabilitation systems that use head motion, voice recognition variedly have also been explored in detail. They were found to be inconvenient as they served either limited usability or non-affordability. This design consists of very minimal numbers of instruments used in order to make it cost-effective and it is also assisted with accelerometer sensor for handling properly. KeywordsEye tracking technology, intelligent wheelchair, I...

2015

Statistics suggests that there are around 40 cases per million of quadriplegia every year. Great people like Stephen Hawking have been suffering from this phenomenon. Our project attempts to make lives of the people suffering from this phenomenon simple by helping them move around on their own and not being a burden on others. The idea is to create an Eye Controlled System which enables the movement of the patient’s wheelchair depending on the movements of eyeball. A person suffering from quadriplegia can move his eyes and partially tilt his head, thus giving is an opportunity for detecting these movements. There are various kinds of interfaces developed for powered wheelchair and also there are various new techniques invented but these are costly and not affordable to the poor and needy people. In this paper, we have proposed the simpler and cost effective method of developing wheelchair. We have created a system wherein a person sitting on this automated Wheel Chair with a camera ...