Eye Movement Controlled Portable Human Computer Interface for the Disabled

Sreekala Manmadhan Department of EEE, Amrita Viswa Vidyapeetham, Amrita School of Engineering, Bengaluru

usreekala@yahoo.com

Abstract-This paper aims at the analysis and design of an interface to control the Mouse Pointer of a PC using the eye movements of the user. The potential difference between cornea and retina is measured and the movements of eyes were detected. The horizontal and vertical eye movement signals were recorded by the five electrodes placed on various locations surrounding the eye and were processed by horizontal and vertical channel amplifiers which consist of bio-potential amplifiers, band-pass filters and dc level shift circuits. Based on the kind of signal, an appropriate data is sent from the microcontroller to the PC serially. Mouse pointer movement in the PC is achieved based on the data received via serial port. Keywords—Electro-oculogram, Mouse Cursor Control

I. INTRODUCTION Eye movements can be traced by recent techniques with

great speed and accuracy. They have many feasible implementations in human-computer interactions as a robust input device. The approximately estimated 170,000 disabled persons are able to control only the muscles of their eyes connected to cornea. Across the globe, several hundreds of people are victims to extreme disabilities such as Amyotrophic Lateral Sclerosis (ALS), brainstem stroke, brain or spinal cord injury, Cerebral Palsy (CP), and muscular dystrophies. These people find it extremely difficult to express themselves through speech or body movement. As per a recent survey conducted, approximate estimates of about 45,000 people are currently affected with ALS. Each year around 10 to 12 in thousand infants is born with Cerebral Palsy. Cerebral Palsy is more common compared to ALS. Several such nervous disorders cause impairment of the whole body except the brain and eye movements. In such cases, the person is left only with the eye movements as a medium to communicate with others.

The Electro-Oculgram (EOG) signals which are obtained due to the eye movements can be used to control various appliances such as wheelchair, computer, fan, television, etc.. Electro-oculography is a method for measuring the resting and active bio-potential of the eye, generating a signal called EOG. These bio-signals generate various patterns for different eye movements like left, right, up and down. EOG potential changes can be measured by the Ag-Ag Cl surface electrodes. EOG signals frequencies are approximately in the frequency band of 0-38Hz and 50-3500 Micro-Volts [1].

As EOG signals are differentially traced in time domain

and it is noise free, Nearest Neighbourhood algorithm is used without the help of any pre-processing. Using this algorithm, the main idea is when a new feature vector, which is similar to the vectors from the training set is detected, it is classified as the same class as most of these vectors. The horizontal and vertical eye movement signals traced by the surface electrodes were then transmitted to a two channel amplifier which consists of Pre-amplifiers, band-pass filters, Shift circuits, Right-leg driven circuits and Power supply [2]. The algorithm works with derivative and amplitude level of electro-oculographic signal. Derivative level is used to find out signal boundaries and the amplitude level is used to remove noise. Corresponding to movement direction, different kinds of events are generated. Events are associated with a movement and its route. A hit rate of approximately 94% is achieved using this technique. An application of Computer Control using ocular movements is implemented using this algorithm [3]. An exhaustive search for previous EOG detection systems showed that there has been no completely successful solution for a completely robust and affordable design. An affordable hardware software system for the differently abled people who cannot use hands is possible with the help of EOG signal so that they can use their eyes to control the mouse. The system using the EOG method can be manufactured at a low price and it is invasive and can be used for a long time.

II.CIRCUIT DESCRIPTION A.Block Diagram

The Electro Oculogram biopotential amplifier’s first stage consists of the instrumentation amplifier which provides the initial amplification. It reduces the effect of signals such as Power-line interference and electro myographic artifacts since it is having high input impedence, high gain and high Common Mode Rejection Ratio (CMRR).For horizontal and vertical channel two separate instrumentation amplifiers are used [3]. A band pass filter is used after the instrumentation amplifier with cut-off frequencies 0.05Hz and 38 Hz, because the EOG signal frequency content varies between DC and 38 Hz. as shown in Fig 1[2].

Fig.1. Block diagram of EOG Acquisition System

978-1-4799-5026-3/14/$31.00 ©2014 IEEE

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Fig. 2.Block Diagram of Digital Signal Processing of EOG

Fig. 3. Circuit Diagram of Analog Signal Processing Module B. Electrodes

Ag-AgCl electrodes are non-toxic because of their stability and reproducibility, and they also make excellent standard and reference electrodes. If surface electrodes were placed superior and inferior to the orbit of each eye, and a reference electrode lateral to the eye of interest, vertical eye movements can be measured. When a test subject is glaring straight ahead, the corneal-retinal dipole is in equal distance between the two electrodes, and then the resulting EOG output is negligible. When the subject looks to the left, the cornea becomes closer to the left lateral electrode, resulting the EOG output to become more positive. When the subject looks towards the right, cornea becomes closer to the right electrode, resulting the electrode potential becomes negative. C. Instrumentation Amplifier

The instrumentation amplifier IC(AD 620) used is a cost effective, noise-free, high precision amplifier and works in low frequency also and requires only one external resistor to set gains of 1 to 10000.The gain equation is given by

D. Low Pass and High Pass Filters

A low-pass filter is an electronic filter that passes low frequency signals and attenuates signals with frequencies higher than the cut-off frequency. An operational amplifier in a conventional non-inverting configuration is used to construct the filter in a Sallen-Key topology. The Sallen–Key topology is an electronic filter topology used to implement second-order active filters that is particularly valued for its simplicity. In this work three second order low pass filters are cascaded to get a sixth order filter.

A high-pass filter is an electronic filter that passes high frequency signals but attenuates signals with frequencies lower than the cut-off frequency. A simple passive first-order electronic high-pass filter is implemented using a combination of resistor and capacitor. A summing amplifier sums several voltages and in our project it is used to shift the signal so that it can be fed to the ADC. LPF Design

Fc=1/(2 RC) Fc=34Hz. C=0.1μF R=47k

HPF Design Fc=1/(2 RC) Fc=0.05Hz. C=100μF.R=35k

E. Digital Signal Processing

Microcontroller can take only digital signals as input. Intel 8051 is used as the microcontroller since it is of low cost. Since signals coming from more than one channel have to be digitized, ADC0809 is used for digitization purpose. It has an inbuilt multiplexer which can select any one of the 8 input channels at a time for digitization. But only 2 of these channels are being used here. The resolution of this ADC is 8 bits and its step size has been set to be 19.53mV.The digitized signal obtained from ADC0809 is compared with previously set threshold values for classifying the signal into different kinds. Based on the kind of signal, an appropriate data is sent from the microcontroller Intel 8051 to the PC serially via RS232 cable. Mouse pointer movement in the PC is achieved using Visual Basic (VB) which is coded to do so based on the data received via serial port.

Fig. 4.Electrode Positioning

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III EXPERIMENTAL RIn order to accomplish gratifying

this technique and to correctly detect the cpoint of the tested subject, several hypotheare made. These are based on the eye movdistance between the tested subject and tcomputer. The system was developed integacquiring hardware and an EOG procesprocessing module implements a trainedescription and coordination system acorresponding control and validation signcomputer interface.

The amplification unit gave an ouinput voltage. The cut-off frequency of t33Hz to eliminate noise. The expected outpuis to reject higher frequencies and noicomponents of low frequencies within thwhich is the admissible range of EOG sifrequency of the Filter (HPF) is 0.05Hz tocomponent. The Figure 5, Figure 6, FigurTable 1 shows the various EOG signaldifferent eye movements. The upper line shchannel output and the down line showoutput.

Fig 5.Left & Right eye movements with DC shift (HorSubject1

Fig.6..Left & Right eye movements with DC shift (Ho movement) Subject2

RESULTS outcomes by using current observation esis and restrictions vements and on the the monitor of the grating EOG signal sing module .The

ed eye movement nd generates the nals in the human

utput 500 times the the Filter (LPF) is ut from the module se and allow the he range of 33Hz ignals. The cut-off o eliminate the DC re 7, Figure 8 and ls associated with hows the horizontal

ws vertical channel

rizontal Eye movement)

orizontal Eye

Fig. 7.Up, Down & Blink eye movemenMovement), Subject1

Fig. 8. Up, Down & Blink eye movemenMovement),Subject2 The microcontroller classifies thon its value. Based on this class‘A’, ‘B’, ‘C’, ‘D’ or ‘E’ is sentof the mouse pointer in the dirreceived from the microcontroll

Fig.9(a). Experiment Setup for Analog S

Fig.9(b).Experiment Setup for Digital S

nts with DC shift (Vertical Eye

nts with DC shift(Vertical Eye

he digital signal acquired based sification, appropriate data like t serially to RS232. Movement ection based on the serial data ler as in Figure 9(a),9(b),9(c).

Signal Processing

Signal Processing

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Fig. 9 (c).Final Experiment Setup

TABLE I

EOG PEAK POTENTIAL OBSERVED FOR THREE SUBJECTS

Subject Up

Down

Left Right

Voluntary Blink

1 300 mV

-300 mV

-500 mV

500mV 900 mV

2 1 V -1 V -1.6 V 1.4 V 2V 3 800

m V -2 V -4 V 3V 3.2 V

IV PERFORMANCE ANALYSIS Performance analysis of the system is based on the accuracy of the system to correctly classify the signal into left, right, up, down movements and blink. Considering the data sets for the movements, taken over a period of time for 50 datasets is given in Table II.

TABLE II

PERFORMANCE ANALYSISE OF EOG FOR MOUSE CURSOR MOVEMENT

Left Right Up Blink Accurate Classification

48 48 41 28

Precision (48/50) 96%

(48/50) 96%

(41/50) 82%

(28/50) 56%

V.CONCLUSION The novel project was designed and the EOG signal acquired was noise-free because of the presence of salient key sixth order filter. EOG signal is traced efficiently, and completely eliminates the DC drifts and power line interferences. A major improvement was achieved over existing EOG systems that have restricted EOG signal processing based applications from being widespread because of the noise. The performance of the entire EOG signal acquisition system was found to be stable and it was much cheaper and thus cost effective. The EOG system is small and portable. The system is user friendly and can be used in extreme harsh environment also. The flexibility in the system’s hardware and software enables further enhancements to the system possible.

VI.FUTURE SCOPE

Eye Tracking Computer User Interface incorporates mainly the construction of an eye tracking hardware using EOG. It also includes precise and accurate tuning in software. This device can be used for many virtual reality systems and video games. Eye blinking is an essential safety system which

shields the eye from the harmful environmental exposure. So eye blink detector is useful. Even for fatigue diagnosis the eye blink is considered to be a suitable indicator for multiple and different tasks of human being activity. For Portable clinical EOG, it is very crucial to study the EOG system in various types of eye movements for scientists due to the plentiful pathological information. Nevertheless, the present commercial Electro Occulogram instrument only delivers very less and rigid eye movement patterns.

REFERENCES

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[2] Xiaoxiang Zheng, Xin Li, Jun Liu, Weidong Chen and Yaoyao Hao,” A portable wireless eye movement-controlled human-computer interface for the disabled”.

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