The Emotional Spectrum Analyser

Report
The Emotional Spectrum Analyser
Benedict Singleton and Dr. Kev Hilton
Centre for Design Research © 2008
Introduction
• ‘Understanding’ changes our beliefs and needs
• From design of effective product interfaces, to affective
products.
• From a historical lack of interest, to perceived
competitive advantage for product innovation.
• This developed a need to reliably quantify emotions and
develop technical solutions.
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Emotional Spectrum Analysis
• ESA16 software, using electro-encephalogram
technology
Contemporary Conceptions
• Emotional state is complex and difficult to articulate
• Often characterised as a blending or layering of core
emotions
• Technologists looked for solutions to provide a ‘Cognitive
representation’ of a ‘Physiological state’.
• However, emotion is led by changing context or situation
and environment, a potentially ‘chaotic’ multi-factorial
system of influence.
Centre for Design Research © 2008
Emotional Spectrum Analysis
Contemporary Conceptions
• ‘Pure’ emotions, e.g. anger or happiness, can still be
used as discussion points around Emotional Space
(Russell and Feldman Barratt, 1999).
• However, mono-dimensional models do not adequately
represent the complexity of emotional evidence for
effective application to design.
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Assessing Emotion Objectively
• ‘Objective’ observation of participant’s emotions is
unreliable.
• Self-report of emotions has also proven unreliable
(Turkkan, 2000).
• Post-hoc categorization of emotions is problematic.
This has led to discussions around ‘universal’ words and
images.
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Assessing Emotion Objectively
PrEmo V5 (Desmet, 2002)
Assessing Emotion Objectively
Kansei Engineering, scaling experience
Happiness
Fast
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X
Sadness
X
Slow
Assessing Emotion Objectively
• These approaches still require ‘reflective’
reporting.
• There is a need to record data in real-time.
• Technology might work in combination with
universals to develop this field of knowledge.
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Physiological Traces of Emotion
• Reliable automatic means of monitoring immersive
experiences.
• ‘Immersion’ and ‘verbalizing’ tasks distract one another.
• Neuroscience technologies, such as ESA may provide
the physical means.
• Universals need to be further developed to provide
reliable cross-cultural categorization.
• However we still face the complexity of influences on
experience.
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Physiological Traces of Emotion
• There is no simple way to map neural activity onto
emotion (Prohovnik et al, 2004).
• The Brain Function Laboratory’s ESA software takes an
orthogonally rotated approach to mapping four
independent and dissimilar forms of neural activity.
• Labeling them with the ‘state’ terms which were
commonly used in self-report.
• It is of course the universality and applicability of these
terms which challenge development.
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Physiological Traces of Emotion
Physiological Traces of Emotion
• Emotional intensity on the recording does not
consistently match the experienced, ‘remembered’,
intensity.
• BFL stated that it is not possible to compare one
individual’s recordings against another individual’s, only
against their own.
Centre for Design Research © 2008
Physiological Traces of Emotion
Conclusion
• The hope of ESA-16 providing a non-invasive emotional
assessment.
• Products do elicit emotional responses but reflection
upon these responses can distort the memory of these
emotions.
• However, designers and technologists first need an
validated model of emotion in order to progress.
Centre for Design Research © 2008
Conclusion
• It was therefore concluded that in the short term, this
technology might be repurposed for monitoring other
physiological changes, used for enquiries into immersive
experiences, for example, computer gaming.
• The ESA-16 might be viewed as a stepping stone
towards a clearer understanding of experiences.
• Nevertheless, a key question for further investigation that
came out of this project was ‘just how reliable are our
emotional responses to product?’
Centre for Design Research © 2008
Dr. Kev Hilton ([email protected])
Centre for Design Research © 2008

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