Systems, Man & Cybernetics - October 2016 - 6

Data Acquisition

Preprocessing

Feature Extraction
and Selection
Translation
Classification or
Decoding
Signal Processing and
Machine-Learning Tools

Figure 1. the components of a bCI system.

Left Target

Right Target

1
0.5
0
(a)
1

0
(b)
Hz

Hz

10

1

30
10
C4

0

20
30
-2

-1

0

1

2

C3

20

20
30
10
20

C4

C3

10

30
-2

3s

-1

0

1

2

3s

(c)

Figure 2. the topologies of a mu-band power for right-/left-hand

motor imagery. (a) the cortex and (b) the scalp. (c) average timefrequency representation maps using minimum-norm estimates in the
frequency domain [99].

6

IEEE SyStEmS, man, & CybErnEtICS magazInE October 2016

of existing BCI that provides motor control is discussed.
The pioneering researchers in BCI have
reviewed the state-of-art techniques in this
area and have reported their findings in [1],
[7]-[9], and [99]. The neurophysiological
phenomenon observed is the modulation of
rhythmic activities (mu, beta, and gamma
rhythms) recorded over the sensorimotor
cortex, termed SMR, by human motor
tasks, such as actual movement, motor
intention, or motor imagery. In bilateral
movement tasks, these modulations are
called event-related (de-) synchronization (ERD/ERS) of mu (8-13 Hz) and beta
(14-26 Hz) rhythms, indicating a decrease
in band powers recorded from contralateral sites and its increase in ipsilateral sites.
Figure 2 demonstrates these cortical rhythmic modulations associated with bilateral
hand motor imagery as reported in [99]. In
addition, the neural phenomena reflected
in slow cortical potentials (SCP), P300 and
event-related potentials with their ability to
generate discrete control commands to an
interfaced device were reported to have a
wide range of usability in BCI. Real-time
motor control was achieved by BCI in
which users learned to modulate their SMR
amplitude [10] and ERD/ERS [11] associated with various limb movement imaginations. The reports in [4], [8], and [12]-[14]
highlighted the developments in SMR-BCI
and the shift of its goal from single-trial
classifications to the design of adaptive,



Table of Contents for the Digital Edition of Systems, Man & Cybernetics - October 2016

Systems, Man & Cybernetics - October 2016 - Cover1
Systems, Man & Cybernetics - October 2016 - Cover2
Systems, Man & Cybernetics - October 2016 - 1
Systems, Man & Cybernetics - October 2016 - 2
Systems, Man & Cybernetics - October 2016 - 3
Systems, Man & Cybernetics - October 2016 - 4
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Systems, Man & Cybernetics - October 2016 - Cover3
Systems, Man & Cybernetics - October 2016 - Cover4
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