Design and implementation of EOG based wheelchair for paralyze patients

The earliest record of use of some kind wheelchair date back to between 6th and 5th century BCE. It is considered to be used as transport vehicle at that time. Nowadays wheelchairs are used by people with disability or medical conditions like Paraplegia (disability to use lower motor or senso

Project Title

Design and implementation of EOG based wheelchair for paralyze patients

Project Area of Specialization

Biomedical Engineering

Project Summary

The earliest record of use of some kind wheelchair date back to between 6th and 5th century BCE. It is considered to be used as transport vehicle at that time.

Nowadays wheelchairs are used by people with disability or medical conditions like Paraplegia (disability to use lower motor or sensory functions), Quadriplegia (severe disability to use all four limbs caused by injury or illness) and other conditions that may cause a person any difficulty to use his motor functions properly.

The development in the field of science and technology has made it possible to find the solutions for medical disabilities. The conventional wheelchairs have been used in the past which require push or pull to move. But now with the autonomous wheelchairs there is no human effort required.

Usually wheelchair is controlled by joystick but for that good mobility of hand is required.  But in case of Quadriplegia or any decease that disables the upper motion of body it is very difficult of the patient to move on his own. A person suffering from paraplegia or quadriplegia or similar disability can gain mobility just by the movement of his eye. Most of people suffering from some kind of disorder or disease can still move their eyes. One of such signal is called EOG. EOG or Electrooculography is a method to detect vertical and horizontal movement of eye.

In this case electrooculography (EOG) technique is employed to process the human eye signal which removes the disability barrier. The wheelchair has two DC motors and a single battery to power the whole setup. The disposable electrodes are used to catch the eye movement signals. The Arduino is used for EOG signal acquisition. This makes it simple and cost effective.

The potential difference between the eyes changes as the gaze changes so the EOG signal is obtained. The four movements are available i.e. forward, backward, leftward and rightward for wheelchair. This classification makes it easier to implement a set of code to move in specific direction. This has enabled the paralyzed patients to get control over their lives.

The EOG signal is received by the Arduino and is translated into voltage levels to move in specific direction. Since the autonomous wheelchairs are costly and cannot serve the needs of most of the middleclass the EOG based wheelchair will be a good alternative.

Project Objectives

The main objective of this work is:

• To develop a wheelchair for the physically impaired patients, this wheelchair can be controlled by the movement of the eye of the disable person.
• To design a low cost signal interface control for wheelchair with high accuracy and reliability for a severely disabled person.
• Our aim to control the wheelchair with the movement of the gaze helping severe paralyzed individuals to regain some mobility.
• Objective of control system is to guide an autonomous robot using by the movement of eyes by the mean of EOG signals

Project Implementation Method

We use the technique of Electrooculography (EOG). EOG is basic biomedical signal in which we obtain the signal from movement of gaze. We will divide our methodology in following steps.

Step 1:

Electrodes placement on eye:

We will place the electrodes around the eye to detect the movement of eye in horizontal and vertical form. These electrodes get signal by Electrooculography (EOG) technique. This eye movement will create micro-potential which is known as EOG signals. We use five disposable electrodes like Ag/Agcl metal electrodes which will place near eye which will obtain the signal from eye but signal is very complex.

Step 2:

AD-620 IC (instrumentation Amplifier gain=2):

We use AD-620 IC which is known as instrumentation amplifier. We get signal from electrodes send to instrumentation amplifier which is use to amplify the very low level signals, interference the signal and reject the noise from the signal.

Step 3:

Notch filter:

Signal get from instrumentation amplifier send to notch filter to remove the line frequency from the signal. Line frequency creates the noise in signal. By using notch filter we will eliminate the line frequency

Step 4:

2nd order Butterworth High pass filter (Cutoff frequency=0.5 Hz):

Signal obtained from notch filter send to high pass filter of cutoff frequency is 0.5 Hz. This filter will eliminate the low frequency from the signal and then pass high frequency above then 0.5 Hz. This filter is also known as 2nd order Butterworth high pass filter.

Step 5:

2-stages cascaded op-amplifier (Gain=200):

Signal get from high pass filter send to 2-stage cascaded op-amplifier which has gain is 200. In this steps this op-amplifier increase the input signal get from high pass filter 200 times increase its values and signal is convert from micro level to desired output signal.

Step 6:

2nd order Butterworth Low pass filter (Cutoff frequency=20 Hz):

Signal receive from 2-stage cascaded op-amplifier send to high pass filter of cutoff frequency is 20Hz. This filter will remove the high frequency from the signal and then pass low frequency less than 20Hz. This filter is also known as 2nd order Butterworth low pass filter.

Step 7:

Aurdino:

We will code the all instruction; instruction is about the movement of motors which is placed on wheelchair. We use aurdino software to code the instruction. Then signal get from low pass filter used in aurdino coding. Coding is related to movement and speed control like left, right, forward, reverse, and stop.

Step 8:

Speed and direction control module:

Instruction in form of signal get from aurdino will send to module. This module controls the speed the direction of motors to move wheelchair motors in desire direction.

Step 9:

Disable and Enable button:

We use disable and enable button which is use to allow the user to moving wheelchair motion through command from EOG technique.

Benefits of the Project

• Development of user friendly interface for partial or fully impaired patients that will help them to fulfill their desire to move without help of anyone else.
• Designing a low cost interface control for wheelchair with high accuracy and reliability for a severely disabled person.
• Easy availability of cost effective wheelchair in Pakistan will not only help poor people of country but also we can sell it to customers in other countries that will effectively increase Pakistan’s economy.
• This project will provide technological advancement in Pakistan after its implementation and completion.

Technical Details of Final Deliverable

• EOG signal receiving module:

This module receive EOG signal from eye, eliminate noise and undesired frequencies and then amplify it according to our desired system requirement i.e. 2V - 5V

• Wheelchair with integrated motors:

Two 12 volts DC motors integrated with the wheelchair controlled via 2 motor drivers to control the speed and direction of wheelchair that is to be connected with Micro controller.

• Battery:

12 volts battery will be installed that will provide the necessary power to run the motors, and is connected to motor delivers.

• Microcontroller :

Microcontroller will cascade EOG module with wheelchair.

Aurdino will receive the signal from EOG module and convert it into instructions that will lead the wheelchair to move according to provided program.

Final Deliverable of the Project

Hardware System

Core Industry

Health

Other Industries

Medical

Core Technology

Wearables and Implantables

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People, Reduced Inequality

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com