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Caracterización de elementos culinarios de la industria de alimentos y

3. METODOLOGÍA DE LA INVESTIGACIÓN

3.5. Análisis situacional

3.5.3. Caracterización de elementos culinarios de la industria de alimentos y

The existene of eletrial ativity in the brain was disovered more than

a entury ago by Rihard Carton [64℄. However, it was not until the early

1920s when EEG was reorded from the human salp for the rst time [65℄.

Nowadays, EEG has beome the most prevalent method for reording brain

ativity for BCI systems.

SalpEEGreordingdisplaysthe diereneineletrialpotentialsbetween

twodierentsites onthehead,superimposingtheerebral ortexthatisloser

tothe reordingeletrode. Theproblemoftheextremelylowamplitudevalues

of the signals attenuated by the several brain layers whih they have to ross

untilreahing thesalpissolved bytheuse ofampliers. Moderntehnologies

allow on-line ltering of the signals and other ontrols to regulate the signal

output. Furthermore, data displays that followaquisition, oera widerange

of options to represent the data for EEG interpretation. Figures 2.8 and 2.9

illustrate some types of EEG reorders available on the market. Figure 2.8

shows a simple Bluetooth based system with two hannels plus another two

hannels for ground and referene. Figure 2.9 shows a more omplex system

of up to 256 hannels omposed by anEEG ap (A) and EEGamplier(B).

2.3.1 EEG eletrodes

Plaementoftheeletrodeshasbeenstandardisedbyusinga10-20systemthat

usesanatomiallandmarksontheskull. Thenameisbasedontheperentages

usedtodeterminetheeletrodeinstallation. Atotalmeasureisdividedinto10

or 20 perent segments. This system uses the distane between the subjet's

betweenthesubjet'sentraloronalplane,thedistanebetweenbothears,for

lateral measurements asis explained in gure2.10. Nasion is the intersetion

of the frontal bone with the two nasal bones. It an be easily deteted as its

loationis the depressed area between the eyes. Inion is the most prominent

projetion of the protuberaneloatedon the lowerrear of the human skull.

Figure 2.8: Example ofEEG portable systemto reordEEG with 2hannels systemplus

groundandreferenehannels.

Eahsite has aname,aletteridentifyingthelobeandanumbertoidentify

the hemisphere. Even numbers orrespond to the right hemisphere and odd

numberstothelefthemisphere. Thedesignations;F p

(frontopolar),F(frontal),

T (temporal), O (oipital), C (entral), and P (parietal) are utilised in the

1020 system as shown ingure 2.10 [66℄.

Furthermore the letter 'z' makes referene to the entral hannels. For

example, the name C z

orresponds to the position at 50% of the nasio-inion

distane and at50% of thedistane between pre-auriularpoints. Thismeans

it is the exat entre point of the salp. The letter C indiates entral and

'z' makesreferene tothe 0% lateraloset fromthe Centraloronal line.

Modern reording systems provide a ap where the eletrode loations are

already predetermined for ease of use as shown in gure 2.9. These modern

systems require aninreased number of eletrodes and as aonsequene they

are plaed on the 10-10 system, meaning that the distane between them is

(A)

(B)

Figure2.9: Figure(A)showsag.teg.GAMMAsyswith64eletrodesappliedand(B)shows

ag.teg.HIamp amplier[67℄. The apandamplier are interonnetedand linked viaa

USBtoaomputer.

Nowadays the variety of tehnologies used to develop EEG sensors overs

a wide range,from wetand dry eletrodes to wireless EEGsensors. However,

allof them pursue the same objetive: tobe preise.

The termweteletrodes isrelatedtotheneedtouseondutingeletrode

gel to attah it to the salp. The materials used for their onstrution are

several: silver/silver-hloride(Ag/AgCl), tin(Sn), gold(Au)orplatinum (Pt)

[68℄. The Ag/AgCl eletrodes are onsidered the golden standard and they

higher quality signals [69℄. However, the need to use a gel inreases the time

needed to plae the eletrodes and an exess of it may reate shorts between

sensors if it spreadsout.

Figure 2.10: EEG10-20systemeletrodeplaementtoshowhowtheeletrodesshould be

plaedusingperentagevaluesofthesizeoftheperson'ssalp. Referenepointsaremarked

in both views: nasion-inion and A 1

-A 2

. (A) Side-view of a person's headwith the10-20

oordinatesoverlaid. (B)Top-downviewofaperson'sheadwiththeeletrodeoordinates

overlaid[70℄.

By ontrast, dry eletrodes are designed to be eient without the need

for ondutive gel. The absene of gel is substituted by moisture onthe skin,

mainly sweat [69℄. Numerous variations of dry sensors exist on the market.

For instane: stainless steel diss or miro-fabriated silion strutures. This

type of eletrode isused mainlyinresearh as they present some problems of

usability for normal linial appliations due to their instability as they are

muh more diultto seureto the patient than wet eletrodes [69℄.

Thereisanother modelofeletrodethat,ontrarytoawetordryeletrode,

does not require diret physial ontat with the skin. Some examples of

these non-ontat sensors an be found in the literature [71, 69℄. They are

omprised of aset of apaitive eletrodes with a wirelesstransmitter tosend

data to a omputer. These systems have the advantage of being insensitive

to skin onditions and require zero preparation. However, their preisionand

reliabilitystillhave not been proven.

For this researh, the eletrodes used are ative Ag/AgCl ring eletrodes

from g.Te [67℄ implanted in the g.GAMMAap previously mentioned and

2.3.2 Clinialbrain wave bands

Hans Berger was the rst investigator to disover a rhythmi brain wave in

the range of 8-12Hz that he named the

α

band [65℄. Sine his disovery, it has been demonstrated that, irrespetive of the natureof the observed signal,

mostofthebrain'sativityhasmultiplefrequeniesthatevolveovertime. The

most important are: the delta, theta, alpha, beta and gamma bands. They

are identied aording to their frequeny and they possess dierent features

that are desribed in table2.2.

Table2.2: SummaryofthemainEEGbrainwavebandsandtheirfeatures[72℄.

Name Frequeny range (Hz) Features Delta (

δ

) 0.5-4

Oursin sleep ora vegetative state of

the brain,slowand high amplitude

waves.

Theta (

θ

)

4-8

Oursduring lightsleep, quiet foused

meditation. They have been observed

duringmemory retrieval.

Alpha (

α

)

8-12

Mediatelevelof onsiousness, relaxed,

awareness of the body, predominant with

losedeyes, prominentabovevisualareas.

Beta (

β

)

12-30

Relatedto onsiousness, busy or

anxious thinkingand ative

onentration. Low voltagewaves.

Gamma(

γ

)

>30

Withhigh level informationproessing,

forlearning and memory.

2.3.3 Artifats

Reording eletrial ativity from the brain is subjet to non-erebral inter-

ferene due to the high sensitivity of EEG systems. Those soures, named

artifats, an have a non-physiologial origin. For example, eletrial devies

operatingnearbyorphysiologialinterferenesignals originatedfromthe sub-

jet's heart and musle movements. Small movements suh as blinking or

frowning an introdue large spikes in the EEG signals and may deeive the

interpreter tobelievethat theapparent souresare abnormal[73℄. In[74℄, the

authors performed a omparativestudy of the eet of blinking on the signal

tonoiseratio(SNR) forsalpEEGandiEEGsimultaneously. Thisshowsthat

Another soureof noise isthe plaement ofthe eletrodes; if the referenes

to plae the ap or eletrodes are not aurate, the reorded EEG signal will

beaeted by noise. Inthe sameway,if one eletrode isunseure itan move

during the experiment ausing large artifats. In addition to these types of

noise, skin-eletrode noise must be onsidered whih strongly orrelates with

the skin impedane. The eet is redued with the use of the gel in the

ase of wet eletrodes but the issue stillremains under-addressed in the ase

of dry eletrodes, although eorts have been made to negate this eet [69℄.

Reognition and eliminationof the artifats in EEG reordings is an arduous

task, but essential forthe development of pratialsystems [73℄.

In the last deade several methodologies have been proposed to improve

the SNR of EEG measurements, espeially those omprising dierent signal

proessing tehniques designed to redue the noise using a range of temporal

averaging shemes. For example median and weighted averaging, trimmed

estimators, wavelet-based de-noising methods or spatial lters [75℄. In order

to eetively hoose the most appropriate method to deal with noise, several

aspets needtobeonsideredinrelationtothe propertiesof the dataand the

researh questions being asked [76℄.

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