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The Emotional Spectrum Analyser. Benedict Singleton and Dr. Kev Hilton. Introduction. ‘Understanding’ changes our beliefs and needs From design of effective product interfaces, to affective products.
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The Emotional Spectrum Analyser Benedict Singleton and Dr. Kev Hilton
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.
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.
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.
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.
Assessing Emotion Objectively PrEmo V5 (Desmet, 2002)
Assessing Emotion Objectively • Kansei Engineering, scaling experience • Happiness Sadness • Fast Slow X X
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.
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.
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.
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.
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.
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?’
