Alternative methods of Human-Computer Interaction

Aleksandra Królak

Alternative methods of Human-Computer Interaction - Aleksandra Królak 2

Human-Computer Interaction

Human Computer

Interaction

2014-06-17

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HCI and other disciplines

HCI

EngineeringArtificial

Intelligence Psychology

ComputerScience

Physiology

Antropology

Ergonomics

Linguistics

Sociology

Art

Philosophy

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Human-machine communication

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Disability in numbers

John Gill, 20092014-06-17

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Vision & Hearing Impairments

Problems:• Low vision• Color vision

impairments• Blind

• Deaf

Solutions:• Magnifier, large font• Color schemes

• Screen readers• Voice recognition• Lip reading systems• Touchplates

• Extended subtitles

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Motor impairments

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Brain-Computer Interface

The goal of BCI technology is to give severely paralyzed people another way to communicate, a way that does not

depend on muscle control [Wadsworth Center]

http://www.ece.ubc.ca

Traditional Definition

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Commercial BCI

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EPOC Emotiv

Neural Impulse Actuator

MindWave Necomimi Brainwave Cat Ears

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SSVEP-based BCIs

FFT

EEG Signal

Frequency [Hz]

Ampl

itude

[uV]

SSVEPs for stimulation frequency and its harmoincs

StimulationA

(f1)C

(f3)B

(f2)

D(f4)

F(f6)

E(f5)

G(f7)

I(f9)

H(f8)

• System developed in Medical Electronics Division, TUL• Steady State Visually Evoked Potential (SSVEP) - natural

responses of brain to visual stimulation at specific frequencies (3.5Hz to 65Hz):

OZ channel or O1, O2 channel pair

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EEG spatial filtering

optimal spatialfilter

Laplacefilter

singlechannel

differentialpair

graphic illustration of the filter coefficients

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Proposed SSVEP detection method

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Eye-controlled HCI

VisionKey

EagleEyes

VISERG

Eye Gaze Interaction

Project

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Eye-blink controlled HCI

System developed in Medical

Electronics Division, TUL PC computer or laptop USB webcam Open source solution:http://b-link.sourceforge.net/

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Eye-blink detection systemImage from

webcamFace and eyes

detection

Eye openess analysis and

eye-blink detection

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Communication via eye-blinks• short (spontaneous) <200ms• long (voluntary) >200ms

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On-screen keyboard

BLINK

C

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System performance

Before training After training

Letter sequence Average time [s] Average time [s]

MAIL 40.1 35.03

NAME 46.2 39.77

MY NAME IS 111.8 93.45

INFORMATION 132.5 100.57

GOOD MORNING 141.3 108.27

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Mouth shape detection systemImage from

webcamFace and mouth

detection

Control gesture (showing teeth) detection

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HCI systems developed by students in Medical Electronics Division

0.00 1.00 2.00 3.00seconds

-0.94

-0.47

0.0

0.47

mV

EMG

(5

- 250

Hz

w/n

otch

)

-0.83

-0.41

0.00

0.41

mV

EMG

(5

- 250

Hz

w/n

otch

)

EMG based Vision-based

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