Design of a Novel Efficient Human–Computer
Interface: An Electrooculoagram Based Virtual Keyboard
出處:IEEE TRANSACTIONS ON INSTRUMENTATION
AND MEASUREMENT, VOL. 59, NO. 8, AUGUST 2010
作者:Ali Bulent Usakli and Serkan Gurkan
報告者:洪家楠
Outline
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1.INTRODUCTION
2.HCIs
3.NEW EOG-BASED SYSTEM
4.RESULTS AND DISCUSSION
5.CONCLUSION
1.INTRODUCTION
 It is assumed that the population of people
aged 60 and beyond will range from one to
three in 2030
 Considering life span extension and the
handicapped, the need for a human–computer
interface (HCI) has been increasing
INTRODUCTION(2)
 Cognitive functions are generally normal,
patients with amyotrophic lateral sclerosis
 Other tetraplegic clinical conditions (e.g.,
the locked-in syndrome) have severe
disabilities in moving their whole bodies.
INTRODUCTION(3)
 Some of these patients can only move their
eyeballs. Establishing a new channel without
overt speaking and hand/arm motions makes
life easier for patients and therefore
improves their life quality.
INTRODUCTION(4)
 Paralyzed stroke patients are unable to
normally communicate with their environment.
 their body that is under their control, in
terms of muscular movement, is their eyeballs.
INTRODUCTION(5)
 As a review of the state of the art of
electrooculogram (EOG) systems, there are
several EOG-based HCI applications for
different purposes in the literature.
 Our motivation is to increase the quality of
life of these patients using an HCI that
provides an efficient communication channel.
2.HCIs(human-computer interface)
 The interface that provides control of
machines for disabled people is called
manmachine interface (MMI) in general.
 If control can be made by using a computerbased (or microcomputer-based) system, it is
called HCI, instead of MMI, which has the
same meaning.
HCI(2)
 The electrical signals generated by the human
brain that are related to body functions are
called an electroencephalogram (EEG).
 If the assistive system is based on EEG, it
is called the brain computer interface (BCI),
and its applications for severely disabled
people are increasing.
HCI(3)
 A. EEG-Based HCI Systems
 B. EOG-Based HCI Systems
 C. EOG Measurement
EEG-Based HCI Systems
 EEG-based systems are the most commonly used
in HCI applications because of the
possibility of noninvasive measurement on the
scalp.
 BCI systems are generally EEG-based systems
and can translate brain activity into
electrical signals that control external
devices.
EEG-Based HCI Systems(2)
 BCI systems can provide a communication and
control channel
 That bypasses conventional neuromuscular
pathways involved in speaking or making
movements to manipulate objects.
EOG-Based HCI Systems
 Electroculography is a technique for
measuring the resting potential of the eye,
and the resulting signal is called EOG.
 These signals show certain patterns for each
kind of eye movement (left, right, up, down,
and blink).
EOG-Based HCI Systems(2)
 An EOG-based virtual keyboard provides a
means for paralyzed patients to type letters
onto a monitor with eye movements without
using the normal keyboard.
 Most of the research in this research field
focused on translating four eye movements
(left, right, up, and down) and eye blink to
select characters from the monitor for typing
onto the screen (i.e., speller).
EOG-Based HCI Systems(3)
 Considering EOG signal properties, EOG-based
HCI systems are more efficient than EEG-based
systems in some cases.
 When light comes to this layer, the nervous
system transmits the signal to the visual
cortex in the brain. The eyes are rotated by
six muscles, and the eyeballs make these
movements.
EOG-Based HCI Systems(4)
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1)
2)
3)
4)
5)
Saccadic
Vergence
Pursuit
Vestibular occular reflex (VOR):
Optokinetic response (OKR):
EOG-Based HCI Systems(5)
EOG Measurement
 Recordings in EOG signal measurement
electrodes
EOG Measurement(2)
 EOG signals are roughly in the band of about
0–100 Hz and 50–3500 μV.
 Measurement and processing of the EOG signal
are easier than those of EEG (< 100 μV)
signals.
 Compared with EEG signals, EOG signals have
greater amplitude.
3.NEW EOG-BASED SYSTEM
 In the design of EOG amplifiers, removing dc
drift and providing signal linearity are the
main research areas.
 In the design of biopotential amplifiers,
saturation due to dc level, dc drift, 50-Hz
(or 60-Hz) power line noise, and other
noises .
NEW EOG-BASED SYSTEM(2)
 1) Subject/patient safety must be provided.
 2) Electronic noise, particularly power line
noise, is reduced as much as possible.
 3) Biological signal originality must be kept.
 4) Electronic noise and electromagnetic
interferences should be considered.
NEW EOG-BASED SYSTEM(3)
NEW EOG-BASED SYSTEM(4)
 1) Two channels for horizontal and vertical eye movements.
 2) Use of Ag/AgCl electrodes.
 3) By using differentiating approaches, the dc level and
power line noise are removed.
 4) 10-bit digital resolution.
 5) μC-based system.
 6) Communication through serial ports.
 7) Event marker ability.
 8) Battery-powered operation.
 9) NN algorithm for classification.
 10) The system is realized with available and economical
components.
NEW EOG-BASED SYSTEM(5)
Electronic Circuitry
Electronic Circuitry(2)
輸入放大器電路
濾掉直流電頻
Electronic Circuitry(3)
NEW EOG-BASED SYSTEM(6)
NEW EOG-BASED SYSTEM(7)
NEW EOG-BASED SYSTEM(8)
NEW EOG-BASED SYSTEM(9)
4.RESULTS AND DISCUSSION
 EOG signal measurements are easier than EEG
signal measurements. Because EOG signals are
caused by muscle motions
 In the design of biopotential measurement
systems, to reject the common-mode signal
RESULTS AND DISCUSSION(2)
 Although EEG-based HCI systems are common,
they are expensive, inefficient, and
impractical, compared with EOG based systems
for patients who are able to move their
eyeballs.
RESULTS AND DISCUSSION(3)
 1) Horizontal and vertical EOG signals are
successfully measured.
 2) The EOG signals for different eye
movements are classified in real time.
 3) The realized virtual keyboard .
V. CONCLUSION
 Crucial factors in the design of an EOG-based
system include subject/patient safety.
 Power line noise reduction, and keeping
signal originality.
CONCLUSION(2)
 These properties are speech ability,
wheelchair control, and robot arm control.
 Speech and device motion control with eye
movement facility is important in making the
life of a severely disabled patient easier.
 Then, the realized system will be tested by
several patients to improve the quality of
the graphic interface for better and quick
selections of the menu options.