Explain what Affective Computer is and describe its significance as an Emerging Technology

In the first part, explain what Affective Computer is and describe its significance as an Emerging Technology. In the second part of your report, summarize one scholarly article related to affective computing. Be sure that the article is scholarly. And use another article other than the one posted

Paper Requirements:

APA style

3 pages (references does not count)

Our emotions play an important role throughout the span of our lives because they enrich
virtually all of our waking moments with either a pleasant or an unpleasant quality.
Cacioppo and his colleagues wrote that “emotions guide, enrich an ennoble life; they
provide meaning to everyday existence; they render the valuation placed on life and
property” (Cacioppo et al. 2001 p. 173), which illustrates that also the relationship with
our physical world is emotional. It therefore doesn’t come as a surprise that consumer
researchers have found that emotions evoked by products enhance the pleasure of buying,
owning, and using them (Hirschman & Holbrook 1982). In addition, it has often been
argued that the experiential or emotional quality of products is becoming more and more
important for differential advantage in the marketplace because products are now often
similar with respect to technical characteristics, quality, and price. In some purchase
decisions, emotional responses may even be a decisive factor. Clearly, the ‘fun of use,’
i.e. the fun one experiences from owning or using a product, belongs to this affective
rather than to the rational domain. The difficulty in studying affective concepts as ‘joy of
use’ or ‘fun of use’ is that they seem to be as intangible as they are appealing. Even more,
rather than being an emotion as such, ‘having fun’ is probably the outcome of a wide
range of possible emotional responses. Imagine, for example, the fun one has when
watching a movie. This person will experience all kinds of emotions, such as fear,
amusement, anger, relief, disappointment, hope, etcetera. Instead of one isolated emotion,
P.M.A. Desmet (in press) Measuring Emotions
Delft University of Technology; Department of Industrial Design
it is the combination of those emotions that contributes to the experience of fun. It is not
implausible that the same applies to other instances of fun, whether it is sharing a joke,
using a product, or interacting with a computer.
Knowledge of the process of emotion, i.e. how emotions are evoked, can enhance our
understanding of what makes us enjoy interacting with a computer or, for that matter,
with any other kind of product. So far, however, little is known about how people
respond emotionally to products and what aspects of design or interaction trigger
emotional reactions. In my view, an instrument that enables us to measure emotional
responses can support the study and exploration of relationships between subjective
affective responses, and objective interaction and design characteristics. Given this
application purpose, the instrument should be able to measure subtle (i.e. low intensity)
emotions, and mixed emotions (i.e. more than one emotion experienced simultaneously).
In addition, our research requires an instrument that is applicable cross-culturally and
therefore language independent.
The quest for instruments to measure emotions has a long history. Traditionally, attempts
to measure emotions have been done in the field of psychology and sociology. More
recently (i.e. the last twenty years), acknowledging the important role of emotions in their
field of research, consumer and marketing researchers have developed instruments which
measure the emotional responses to advertisement and consumer experiences. Even more
recently (i.e. the last ten years), and as a result of the rapid invasion of computers into our
daily lives, computer science has also become a player in the field of measurement of
emotions. Unfortunately, none of these developed instruments appears to be applicable
for the measurement of emotional responses to products because none meets all the above
stated requirements. Given the limitations of existing instruments for the current
measurement aims, a new instrument was developed: the Product Emotion Measurement
instrument (PrEmo). This development was an iterative design process. Over a period of
five years, six versions of the instrument have been created. The creation of each version
was followed by an evaluation of its strengths and weaknesses, and on the basis of this
evaluation renewed starting points were defined. Each subsequent version was designed
to correct the flaws of the previous version. This chapter presents the development,
validation, and application possibilities of the sixth PrEmo version. Note that the
development of all PrEmo versions is reported in detail in Desmet (2002). Earlier
versions have also been discussed in previous publications (see e.g. Desmet & Hekkert
1998; Desmet, Overbeeke, & Tax 2001; Desmet, Hekkert, & Jacobs 2000).
Before one can measure emotions, one must be able to characterise emotions and
distinguish them from other states. Unfortunately, this is a problem that currently belongs
to those yet unsolved. Although the concept of emotion appears to be generally
understood, it is surprisingly difficult to come up with a solid definition. When surveying
emotion research in psychology, one finds various traditions that hold different views on
P.M.A. Desmet (in press) Measuring Emotions
Delft University of Technology; Department of Industrial Design
how to go about defining, studying, and explaining emotions. The last 100 years,
psychologists have offered a variety of definitions, each focussing on different
manifestations or components of the emotion. As there seems to be no empirical solution
to the debate on which component is sufficient or necessary to define emotions, at present
the most favoured solutions is to say that emotions are best treated as a multifaceted
phenomenon consisting of the following components: behavioural reactions (e.g.
approaching), expressive reactions (e.g. smiling), physiological reactions (e.g. heart
pounding), and subjective feelings (e.g. feeling amused). Each instrument that is claimed
to measure emotions in fact measures one of these components. As a consequence, both
the number of reported instruments and the diversity in approaches to measure emotions
is abundant. Today’s instruments range from simple pen-and-paper rating scales to
dazzling high-tech equipment that measures brain waves or eye movements. In this
chapter, the distinction is made between non-verbal (objective) instruments and verbal
(subjective) instruments.
2.1 Non-verbal instruments to measure emotions.
This category comprises instruments that measure the either the expressive or the
physiological component of emotion. An expressive reaction (e.g. smiling or frowning) is
the facial, vocal, and postural expression that accompanies the emotion. Each emotion is
associated with a particular pattern of expression (Ekman 1994). For example, anger
comes with a fixed stare, contracted eyebrows, compressed lips, vigorous and brisk
movements and, usually, a raised voice, almost shouting (Ekman & Friesen 1975).
Instruments that measure this component of emotion fall into two major categories: those
measuring facial and those measuring vocal expressions. Facial expression instruments
are based on theories that link expression features to distinct emotions. Examples of such
theories are the Facial Action Coding System (FACS; Ekman & Friesen 1978), and the
Maximally Discriminative Facial Moving Coding System (MAX; Izard 1979). Generally,
visible expressions captured on stills or short video sequences are analysed. An example
is the Facial Expression Analysis Tool (FEAT; Kaiser & Wehrle 2001). Also subtle
expressions, invisible to the naked eye, can be measured because the facial muscle
activity of these expressions result in electrical potentials (facial electromyographic
activity: EMG). This EMG activity can be assessed by determining the voltage from two
electrodes placed on the skin’s surface over a particular muscle group (see Cacioppo &
Petty 1989). Like the facial expression instruments, vocal instruments are based on
theories that link patterns of vocal cues to emotions (e.g. Johnstone & Scherer 2001).
These instruments measure the effects of emotion in multiple vocal cues such as average
pitch, pitch changes, intensity colour, speaking rate, voice quality, and articulation.
A physiological reaction (activation or arousal, e.g. increases in heart rate) is the
change in activity in the autonomic nervous system (ANS) that accompanies emotions.
Emotions show a variety of physiological manifestations that can be measured with a
diverse array of techniques. Examples are instruments that measure blood pressure
responses, skin responses, pupillary responses, brain waves, and heart responses.
Researchers in the field of affective computing are most active in developing ANS

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