EMOTION BASED COMPUTING

By,

SHILPA MARY GEORGE

Roll no : 81

Reg no : 12120082

Guide : Mrs. SHEENA S

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INDEX

1) What is Affective Computing?

2) Objectives

3) Psychological Theories of Emotion

4) Classes of Expressions

5) Components of Emotion

6) A-V-S Emotion Model

7) Electroencephlography (EEG)1) Principles of EEG

2) Applications

3) Major Components

4) Limitations

8) Conclusion

9) References3

WHAT IS AFFECTIVE COMPUTING ?

Affective Computing :

field of research in AI dealing with emotions and machines.

the study and development of systems and devices that can

* recognize,

* interpret,

* process,

* and simulate human affects.

an interdisciplinary field spanning computer science, psychology, and cognitive science.

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OBJECTIVES

To develop a computing device with its capacity togather cues to user emotion from a variety of sources.

-produce “emotion aware machines”.

Can you quantify Fear? Can you tell whether I am afraid?

How often have you used Emoticons in chat messages? Did you feel hampered without them?

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PSYCHOLOGICAL THEORIES OF EMOTION

LOVE

SUBMISSION

AWE

AGGRESIVENESS REMOTE

DISSAPPOINTMENT

JOY

ANTICIPATION

ANGER DANGER

SADNESS

ACCEPTANCE FEAR

SURPRISEJOY

ANTICIPATION

ANGER DANGER

SADNESS

ACCEPTANCE FEAR

SURPRISE

OPTIMISM

CONTEMPT

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CLASSES OF EXPRESSIONS

Broadly classified into happy, sad, disgust, fear, anger,

surprise and neutral.

Goal is to classify an unknown expression into one of

these classes

Facial expression, posture, gesture, speech, force or

rhythm of key stroke, temperature change of hand on

mouse can signify changes in user’s. emotional state,

detected and interpreted by a computer

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COMPONENTS OF EMOTIONS

Subjective experience (feeling of fear and so on).

Physiological Changes in Autonomic NervousSystem(ANS) and Endocrine System (Glands andHormones released from them).

- e.g. trembling with fear precedes conscious control ofthem

Behavior evoked (such as running away or fainting dueto fear)

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[A,V,S] EMOTION MODEL

[Arousal , Valence , Stance] :- A 3-tuple models an

“emotion”.

Arousal:- Surprise at high arousal, fatigue at low

arousal

-the intensity with which the emotion is experienced

Valence:- Content at high valence, Unhappiness at

low valence

-the discrimination between positive and negative

experiences

Stance:- Stern at closed stance, accepting at open

stance9

ELECTROENCEPHLOGRAPHY (EEG)

A medical imaging technique

A measurement of the electrical activity of the brain

The recording of the brain’s spontaneous electrical activity over a short period of time, usually 20-40 mins, as recoded from multiple electrodes placed on the scalp.

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PRINCIPLES OF EEG

The brain’s electrical charge is maintained by billions ofneurons.

Neurons pass signals via action potential created byexchange between sodium & potassium ions in and out ofthe cell- Volume conduction

When the wave of ions reaches the electrodes on thescalp, they can push or pull electrons on the metal on theelectrodes, the difference in push, or voltage, betweenany two electrodes can be measured by a voltmeter whichover time gives us the EEG

Scalp EEG activity shows oscillations at a variety offrequencies. Several of these oscillations havecharacteristic frequency ranges, spatial distributions andare associated with different states of brain functioning.

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APPLICATIONS

Monitor alertness, coma and brain death

Locate areas of damage following head injury, stroke, coma etc.

Test afferent pathways (by evoked potentials)

Monitor cognitive engagement (alpha rhythm)

Control anaesthesia depth

Investigate epilepsy and locate seizure origin

Test epilepsy drug effects

Monitor human and animal brain development

Test drugs for conclusive effects

Investigate sleep disorder and physiology12

MAJOR COMPONENTS

Electrodes with conductive media

Amplifiers with filters

A/D converter

Recording device

• electrodes read signals from head surface

• amplifiers bring microvolt signals to the range where they can be digitalized accurately

• converter changes signals from analog to digital

• Personal computer stores and displays obtained data

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RECORDING ELECTRODES

Types of electrodes :

Disposable (gel-less, and pre-gelled types)

Reusable disc electrodes (gold, silver or tin)

Headbands and electrode caps

Saline-based electrodes

Needle electrodes

• Electrode caps are preferred with certain number of electrodes installed on its surface.

• Needle electrodes are used for long recordings and are invasively inserted under the scalp.

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Electrode locations and names are specified by the international 10-20 system

Label 10-20 designates proportional distance in percents between ears and nose where points for electrodes are chosen.

Electrode placements are labelled according to adjacent brain areas : F(frontal), C(central), T(temporal), P(posterior), and O(occipital).

The letters are accompanied by odd nos at the left side of the head and with even nos on the right side.

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Electrode Cap

Labels for points16

LIMITATIONS OF EEG

Poor spatial resolution

Most sensitive to a particular set of post synaptic potentials, those generated in superficial layers of the cortex, in dendrites and deep structures or producing currents that are tangential to the skull.

It is mathematically impossible to construct a unique Intracranial current source for a given eeg signal as some currents produce potentials that cancel each other out –inverse problem.

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AREAS OF AFFECTIVE COMPUTING

AFFECTIVE WEARABLES

Sensors & tools can be used in recognizing affective patterns,but these tools require a lot of attention/ maintenance.

Figure : Wearer’s Blood Volume

Pressure using

photoplethysmography

Figure : Sample & transmit

biometric data to larger

computer for analysis

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AREAS OF AFFECTIVE COMPUTING

EXPRESSING EMOTION:

Figure : MS Office Assistant Figure : Kismet Robot

Evolution over

the years

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KISMET

an expressive robot at MIT is equipped with auditory and proprioceptive (touch) sensory inputs.

can express emotion through

*vocalization

* facial expression and adjustment of Gaze

*direction & head orientation.

Recognise stimuli

Realistic

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CONCLUSION

Affective Computing is a young field of research

•For interactive systems, something far better than the

current crop of “intelligent” systems are needed.

•Affective Computing has applications in improving the

quality of life in impaired people (successfully

demonstrated for Autism)

•Ethical compromises need to be done to inculcate affective

computers

•This field can really benefit from research into the human

brain/mind.

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REFERENCES

1. R.W. Picard (1995), "Affective Computing“,MITMedia Lab

2. R.W. Picard (1998) , “Towards Agents that recognize emotions”, Actes Proceedings, IMAGINA

3. http://www.ai.mit.edu/projects/humanoid-robotics-group/kismet/kismet.html

4. Automatic Facial Expression Recognition using Linear and Non-Linear Holistic Spatial Analysis, Ma and Wang (2005)

5. Emotion and Reinforcement : Affective Facial Expressions facilitate Robot Learning, JoostBrokens (2007)

6. Emotion Recognition Based on Brain-Computer Interface Systems- Taciana Saad Rached and Angelo Perkusich 22

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QUERIES ??

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