Systems, Man & Cybernetics - April 2017 - 10
60
40
20
× 10-3
2.5
0
-20
-40
-60
-15 -10
-5
0
5
10
15
20
25
Heart Rate
Global Typicality
Skin Conductance
Methodology
variability between individuals and
the limitations of the one-size-fitsThis is the first such
all type of averages usually used in
Empirical Data Analytics
comprehensive model
traditional statistical approaches
Due to space and other limitations,
where the responses of a group of
we will not introduce details of the
within a cybernetics
people are being modeled.
EDA computational framework. Its
frame.
We do not detail the decisionmain distinctive feature is that,
making and (re)action phase, which
without the need for prior assumpis conscious and follows the protions about the data distributions,
cess at the second layer of the hierthe amount of data, their depenarchical layered structure we propose. Instead, our focus
dence or independence, or even their randomness or deteris on the first phase, phase A, which may take place subministic nature, we can directly (without iterative cycles and
consciously (and thus in an unsupervised manner) and
loops, in a recursive manner) derive multimodal typicality
where perceptions of individuals are formed and emotions
distributions that have the same properties as the pdf, e.g.,
expressed. We further simplify the real-life case by considthat integrate to one [20]-[22]. With the EDA framework, one
ering only simple (noncomposite) concepts (e.g., positive
can partition the collected experimental data and group them
and negative) and only the steady-state model (not traninto data clouds. These can then be labeled, for example,
sient and dynamic).
emotional state 1, emotional state 2, and so on (see Figure 4,
where the values are centered using the subtracted mean).
Furthermore, continuous global typicality can be built
100
(Figures 5 and 6), which is a measure of likelihood and is
Individual 1
fully based on the observed data samples without making
80
Individual 2
any prior assumptions. In fact, if the distance metric that
ES 1
2
1.5
1
ES 2
0.5
0
20
Figure 3. the observed PVs of individual 1 and
individual 2.
0
Heart Rate
100
-20
40 60
20
0
-20
-40
-60
Skin Conductance
(a)
× 10-4
8
60
40
Global Typicality
Skin Conductance
80
20
0
-20
2
20
-10
-5
0
5
10
15
20
25
Heart Rate
Data Cloud 1-Individual 1
Data Cloud 2-Individual 1
Focal Points-Individual 1
Data Cloud 1-Individual 2
Data Cloud 2-Individual 2
Focal Points-Individual 2
Figure 4. the data clouds formed based on the PVs
in Figure 3.
10
ES 1
4
0
-40
-60
-15
ES 2
6
IEEE SyStEmS, man, & CybErnEtICS magazInE A pri l 2017
0
Heart Rate
-20
(b)
50
0
-50
Skin Conductance
Figure 5. the three-dimensional continuous global
typicality built based on individuals' data as
described in [22]: (a) individual 1 and (b) individual 2.
ES: emotional state.
Table of Contents for the Digital Edition of Systems, Man & Cybernetics - April 2017
Systems, Man & Cybernetics - April 2017 - Cover1
Systems, Man & Cybernetics - April 2017 - Cover2
Systems, Man & Cybernetics - April 2017 - 1
Systems, Man & Cybernetics - April 2017 - 2
Systems, Man & Cybernetics - April 2017 - 3
Systems, Man & Cybernetics - April 2017 - 4
Systems, Man & Cybernetics - April 2017 - 5
Systems, Man & Cybernetics - April 2017 - 6
Systems, Man & Cybernetics - April 2017 - 7
Systems, Man & Cybernetics - April 2017 - 8
Systems, Man & Cybernetics - April 2017 - 9
Systems, Man & Cybernetics - April 2017 - 10
Systems, Man & Cybernetics - April 2017 - 11
Systems, Man & Cybernetics - April 2017 - 12
Systems, Man & Cybernetics - April 2017 - 13
Systems, Man & Cybernetics - April 2017 - 14
Systems, Man & Cybernetics - April 2017 - 15
Systems, Man & Cybernetics - April 2017 - 16
Systems, Man & Cybernetics - April 2017 - 17
Systems, Man & Cybernetics - April 2017 - 18
Systems, Man & Cybernetics - April 2017 - 19
Systems, Man & Cybernetics - April 2017 - 20
Systems, Man & Cybernetics - April 2017 - 21
Systems, Man & Cybernetics - April 2017 - 22
Systems, Man & Cybernetics - April 2017 - 23
Systems, Man & Cybernetics - April 2017 - 24
Systems, Man & Cybernetics - April 2017 - 25
Systems, Man & Cybernetics - April 2017 - 26
Systems, Man & Cybernetics - April 2017 - 27
Systems, Man & Cybernetics - April 2017 - 28
Systems, Man & Cybernetics - April 2017 - 29
Systems, Man & Cybernetics - April 2017 - 30
Systems, Man & Cybernetics - April 2017 - 31
Systems, Man & Cybernetics - April 2017 - 32
Systems, Man & Cybernetics - April 2017 - 33
Systems, Man & Cybernetics - April 2017 - 34
Systems, Man & Cybernetics - April 2017 - 35
Systems, Man & Cybernetics - April 2017 - 36
Systems, Man & Cybernetics - April 2017 - 37
Systems, Man & Cybernetics - April 2017 - 38
Systems, Man & Cybernetics - April 2017 - 39
Systems, Man & Cybernetics - April 2017 - 40
Systems, Man & Cybernetics - April 2017 - 41
Systems, Man & Cybernetics - April 2017 - 42
Systems, Man & Cybernetics - April 2017 - 43
Systems, Man & Cybernetics - April 2017 - 44
Systems, Man & Cybernetics - April 2017 - 45
Systems, Man & Cybernetics - April 2017 - 46
Systems, Man & Cybernetics - April 2017 - 47
Systems, Man & Cybernetics - April 2017 - 48
Systems, Man & Cybernetics - April 2017 - 49
Systems, Man & Cybernetics - April 2017 - 50
Systems, Man & Cybernetics - April 2017 - 51
Systems, Man & Cybernetics - April 2017 - 52
Systems, Man & Cybernetics - April 2017 - 53
Systems, Man & Cybernetics - April 2017 - 54
Systems, Man & Cybernetics - April 2017 - 55
Systems, Man & Cybernetics - April 2017 - 56
Systems, Man & Cybernetics - April 2017 - Cover3
Systems, Man & Cybernetics - April 2017 - Cover4
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