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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5276_Библиотеки_им_академика_М_И_Перельмана
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(a) (b)
Figure 2.5: Working principle of the P300 speller. a) Example for a symbol matrix can be used in the P300
speller. Flashes of rows/columns are used as stimuli. The stimuli are numbered from 1 to 12. b) A random
stimulus sequence. E.g. if the user stares at the letter ’B’, a P3b will be evoked for stimuli 2 and 7 [29].
Since the work of Farwell and Donchin, several researchers have proposed extensions
and modifications of the basic P300 speller paradigm. The effect of different matrix sizes on the
amplitude and latency of the P300 wave is tested in [14]. Matrices of size 4×4, 8×8, and 12×12
were presented to the users. Instead of single symbols, the entries in the matrix were diagrams, i.e.
pairs of letters. The study has reached to results state the P300 latency decreased and amplitude
increased as matrix size was increased. Note that this is in line with the relation between target
probability and P300 amplitude as we described in the previous section: the smaller the target
probability is the higher the P300 amplitude is. In this study, classification of P300 waves and
consequently the automatic detection of the symbol the user wanted to select was not attempted.
Another modification of the basic P300 speller, the so-called single display paradigm,
was proposed in [20]. In this proposed BCI system, instead of flashing the whole rows and
columns of the symbols matrix, single symbols were used as stimuli. This has the effect of
reducing the probability for the target stimulus. In the original P300 speller paradigm the target
probability is 1/6 = 0.16, while in the single display paradigm it is 1/36 ≈ 0.03. In their
experiments, the lower target probability led to higher P300 amplitudes and better classification
accuracy than in the basic P300 speller.
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Recently, a novel P300-based BCI stimulus presentation paradigm was presented in [31]
called the checker board paradigm (CBP). In this study, the assumption was that the CBP will
produce superior performance as compared to the row-column paradigm (RCP) because it avoids
the adjacency-distraction and double-flash errors to which the RCP is prone. Additionally, the
study expanded the matrix to an 8x9 matrix which allowed the inclusion of both alphanumeric
keys and function keys, giving the participants more control and communication options. The
larger matrix should also produced larger P300 amplitudes for the target items because the
probability of the target stimulus occurring is reduced. Also, while the larger matrix increases the
time needed for each selection, it should increase the information transferred per selection. The
results showed that the CBP is markedly superior to the RCP in performance and user
acceptability and the CBP has the potential to provide a substantially more effective BCI than the
RCP. This is especially important for people with severe neuromuscular disabilities.
2.5.2 Cursor Control
A P300-based BCI system was presented in 1995 by Polikoff et al., [37] for another control
application. The idea behind the described system is to allow users to control a 2D cursor with the
help of the P300 wave. To implement this idea a fixation cross with target arms in the north, east,
south, and west directions was displayed on a monitor. At the end of each arm small crosses were
displayed and temporarily replaced by asterisks. The replacement of crosses occurred in a random
sequence, and to move the cursor in a given direction subjects were instructed to count the
number of asterisks appearing at the corresponding target arm. While in this study actual cursor
movement was not implemented, an offline analysis showed that cursor control with the help of
the P300 was in principle possible.
The cursor control paradigm was further explored in [28]. Flashing arrows were
displayed in the peripheral area of a screen and subjects could move a cursor by concentrating on
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one of the arrows. The proposed system was tested with five severely handicapped and seven
able-bodied subjects. The study found that handicapped as well as able-bodied subjects were able
to control cursor movement with their P300 wavs. The communication speed achieved by the
severely handicapped subjects was significantly lower than that of the able-bodied subjects.
Nevertheless, this study was one of the first studies showing that P300-based communication is
possible for severely handicapped subjects.
Recently, a P300-based BCI system was developed in [67] to control the movement of
the computer cursor on a computer screen. On the LCD screen, the cursor was displayed with the
surrounded eight small circles, each of which was blinked sequentially in a random order (see
figure 2.6). Five healthy subjects were requested to gaze a tone of the circles placed in the
preferred direction. The P300 activities elicited by the random blink of the target circle were
detected by pattern classifier and they were used to move the cursor to the same direction as the
target circle. It was shown that all of the subjects could control the movement of the cursor to
their preferred direction by moving their gaze point in a short distance.
Blinking of right circle P300 detected?
Yes No
Figure 2.6: Schematic diagram of the visual stimuli. Visual stimuli consisted of the computer cursor and
the surrounding eight open circles. If the P300 elicited by the blink of one of the circles was detected, the
cursor and surrounding circles were moved to the same direction of the blinked circle [67].
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2.5.3 Wheel Chair Control
A sophisticated wheelchair system has been recently developed in [38], where a virtual
reconstruction of the surrounding environment (as inferred from laser range scanner data) is
displayed with a set of points in the free space that can be selected using a P300- based BCI (see
figure 2.7), and these short term goals are reached automatically. Stimuli are randomly flashed in
a row/column manner and the user should pay attention to the stimulus corresponds to the
required action to perform this action.
(a)
(b)
Figure 2.7: A brain controlled wheelchair [38]. (a) A snapshot of a participant navigating along a corridor.
(b) Information represented in the visual display, which is an environment abstraction displayed from the
users point of view. The user can select which goal to reach using a P300 BCI.
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2.5.4 Environment Control
A P300-based BCI system that is used to control electrical appliances in a virtual environment is
proposed in [80] (see figure 2.8 below). Users were facing a laptop screen on which six images
were displayed. The images showed a television, a telephone, a lamp, a door, a window, and a
radio. The images were flashed in random sequences, one image at a time. Each flash of an image
lasted for 100 ms and during the following 300 ms none of the images was flashed, i.e. the ISI
was 400 ms. The EEG was recorded at 2048 Hz sampling rate from thirty-two electrodes placed
at the standard positions of the 10-20 international system. The study showed that significant
accuracy was achieved and users could control the appliances.
Figure 2.8: The display used for evoking the P300 wave [80]
2.6 Review of Available Low-Cost EEG Sensors and BCIs
2.6.1 Overview
Today, new neuro headsets such as the Emotiv Epoc attract many researchers and hobbyists and
may soon allow the use of EEGs for the several consumer tasks. In fact, they are already very
affordable today compared to $20,000-250,000 for historical EEG brain sensing technology.
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In a recent study different non-invasive low-cost EEG systems have been compared with
each other in terms of price and functionality and rated by their usability [41]. Table 2.1 lists
some of the non-invasive BCI EEG acquisition hardware under US$1000 ordered into three
groups of those less than US$200, those between $200 and $501 and those between $500 and
$1000.
Figure 2.9 shows the calculated scores for each selected EEG device normalized to 10. In
their study the Emotiv Epoc showed the highest score in terms of usability and it was ranged in
the middle price segment. Emotiv group have developed two special editions of their products for
developers and researchers wishing to conduct EEG research leveraging the Emotiv EPOC
technology. These editions allow researchers to acquire real-time EEG and EOG raw data so they
can implement their specific applications.
Price Range
Device Name
Data acquired from
# of electrodes
Interface
200
Modular EEG
Raw EEG
2 - 6
RS232
--
Neurosky, Mindset
Raw EEG/Classifi. Data
3
Bluetooth
200 - 500
OCZ Tech., NIA
Classification Data
3
USB
Emotiv, Epoc
Raw EEG/Classification
14
Bluetooth
500 - 1000
Neurobit lite
Classification Data
3
Wireless
Pocket Neurobics
Raw EEG
2
Wireless
Pendant EEG
2
USB
Teunis van Beelen’s
open EEG
Raw EEG
12
RS232
Psychlab EEGx4
Raw EEG
4
USB
Table 2.2: The cheapest EEG acquisition hardware for on-line BCI systems [41]
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Figure 2.9: Tentative scale for the usability score of 8 low-cost EEG acquisition devices [41]
In addition to the above inexpensive EEG systems, recently NeuroFocus Company has
revealed the first dry, wireless full brain EEG headset named Mynd (see figure 2.10). The
company claims they have successfully combined the accurate and reliable performance levels of
gel-based wired EEG systems used in clinical settings with lightweight, attractive design as well
as high durability and serviceability [58].
Figure 2.10: NeuroFocus Mynd
TM
headset [58]
Within seconds of slipping the user-friendly headset on, a consumer’s brainwave activity
is captured across the full cortex. It uses dry “smart” electrodes, eliminating the use of gels and
enhancing signal quality by introducing novel technological breakthroughs. It captures 2000
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samples per sec and sends the data wirelessly using Bluetooth [58]. Currently, the headset is not
available for consumers, but the company promised that it will be soon available with reasonable
price after carrying out the required tests and validations. In addition, the headset documentations
and manuals have not been yet published.
Since we are using the Emotiv Epoc headset as an EEG sensor, in the following subsection we
give more details about it and its SDK.
2.6.2 Emotiv Epoc Headset
The Emotiv Epoc Neuro-headset is a low cost Brain Computer Interface device that has been
developed to be used as a controller for gaming purposes. It consists of 14 EEG electrodes as in
figure 2.11. The electrodes are placed on the scalp according, or similar, to the international 10-
20 format. The headset can sample the data at the rate of 2048 Hz, but the data is internally
downsampled to 128 Hz. The device is connected to the computer using a Bluetooth interface [26]
(more details about Emotive system can be found in [26]). It also has a two-axis gyro for
measuring head rotation.
Since the device has been created for gaming purposes as mentioned above, arrangements
have been made so that the system follows real-time requirements. The device does not require a
separate amplifier unit which reduces the cost drastically and allows mobility for the user.
(a) (b)
Figure 2.11: Emotiv Epoc: a) The headset; b) Electrodes positions on the head [26]
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Emotiv Company provided an SDK with the headset to be used for different applications. Figure
2.12 below shows the control panel of the SDK.
Figure 2.12: Emotiv SDK control panel [26]
The SDK can measure four categories of inputs [26] which are described below:
Cognitiv suite (Conscious thoughts): Imagination of 12 kinds of object’s movement. These
are 6 directions (left, right, up, down, forward, and "zoom") and 6 rotations ([anti-]clockwise
rotation, turn left and right, and backward and forward). Additionally, one other visualization
command "disappear" that can be detected in µ rhythms is provided. While the current driver
may only be able to listen for any 4 of these actions at a time, the degree of freedom is larger
than a joystick's.
Affectiv suite (Emotions): "Excitement", "Engagement/Boredom", "Meditation", and
"Frustration" can be measured by the headset. Emotiv admits that the names may not
perfectly reflect exactly what the emotion is, and says that they may be renamed in the future.
Expressiv suite (Facial expressions): Individual eyelid and eyebrow positions, eye position
in the horizontal plane, smiling, laughing, clenching, and smirking can be detected by the
headset. The expressions are detected by the sensors picking up signals of facial muscles,
rather than by reading brainwaves. Unlike reading mental activity, these detections are very
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fast (10ms) [26] conveying a decisive advantage and rendering them suitable for fast paced
games.
Head rotation: The angular velocity of user’s head can be measured in the right, left, forward,
and backward (but not roll) directions. This is detected by gyros installed in the headset and
not related to the EEG signals.
In addition, EPOC can be used to get the raw EEG data either directly from the headset using
EmoEngine library or from a program provided with the research edition of the SDK called
TestBench. Some hackers tried to get the raw EEG data with the Python Emokit without the need
for EPOC's proprietary software. In all cases, Research, Research Plus or Enterprise Plus SDK
license is needed for reading EEG raw data. The headset is easy-to-use and electrodes do not need
any kind of gel to be wet, only salt water is needed for this.
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