Functional brain imaging techniques that are designed to measure an aspect of brain function can be employed to obtain tangible information related to brain activity. Electroencephalogram (EEG) is one such technique, which measures the electric fields that are produced by the activity in the brain. From EEG measurements, it is possible to extract information and determine the intent of the user for a number of different mental activities (such as motor imagery, motor planning), using a variety of electrophysiological signals such as slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronal activity recorded by implanted electrodes.
The use of EEG for the communication of intent is one of the bases of Brain-Computer Interface (BCI) research, which is geared towards the development of systems to afford people with disabilities or severe neuromuscular disorders the capability of basic communication (by operating word processing programs or through neuroprostheses). EEG signals acquired during mental activities can also be used for subject identification to create a more secure environment for applications such as BCIs, game play, or silent communication.Code has been successfully tested on UCI EEG Database. This database contains measurements from 64 electrodes placed on the scalp sampled at 256 Hz (3.9-msec epoch) for 1 second. Functional brain imaging techniques that are designed to measure an aspect of brain function can be employed to obtain tangible information related to brain activity. Electroencephalogram (EEG) is one such technique, which measures the electric fields that are produced by the activity in the brain.
From EEG measurements, it is possible to extract information and determine the intent of the user for a number of different mental activities (such as motor imagery, motor planning), using a variety of electrophysiological signals such as slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronal activity recorded by implanted electrodes. The use of EEG for the communication of intent is one of the bases of Brain-Computer Interface (BCI) research, which is geared towards the development of systems to afford people with disabilities or severe neuromuscular disorders the capability of basic communication (by operating word processing programs or through neuroprostheses).
Eeg Software Tutorial
EEG signals acquired during mental activities can also be used for subject identification to create a more secure environment for applications such as BCIs, game play, or silent communication.Code has been successfully tested on UCI EEG Database. This database contains measurements from 64 electrodes placed on the scalp sampled at 256 Hz (3.9-msec epoch) for 1 second.
Electroencephalography ( EEG) is an monitoring method to record electrical activity of the. It is typically noninvasive, with the placed along the, although invasive electrodes are sometimes used, as in. EEG measures voltage fluctuations resulting from within the of the. Clinically, EEG refers to the recording of the brain's spontaneous electrical activity over a period of time, as recorded from multiple placed on the scalp.
Diagnostic applications generally focus either on or on the of EEG. The former investigates potential fluctuations time locked to an event, such as 'stimulus onset' or 'button press'. The latter analyses the type of (popularly called 'brain waves') that can be observed in EEG signals in the frequency domain.EEG is most often used to diagnose, which causes abnormalities in EEG readings. It is also used to diagnose, depth of,. EEG used to be a first-line method of diagnosis for, and other focal brain disorders, but this use has decreased with the advent of high-resolution anatomical imaging techniques such as (MRI) and (CT).
Despite limited spatial resolution, EEG continues to be a valuable tool for research and diagnosis. It is one of the few mobile techniques available and offers millisecond-range temporal resolution which is not possible with CT, PET or MRI.Derivatives of the EEG technique include (EP), which involves averaging the EEG activity time-locked to the presentation of a stimulus of some sort (visual, or auditory). (ERPs) refer to averaged EEG responses that are time-locked to more complex processing of stimuli; this technique is used in, and research. In 1875, (1842–1926), a physician practicing in, presented his findings about electrical phenomena of the exposed cerebral hemispheres of rabbits and monkeys in the. In 1890, Polish physiologist published an investigation of spontaneous electrical activity of the brain of rabbits and dogs that included rhythmic oscillations altered by light.
Beck started experiments on the electrical brain activity of animals. Beck placed electrodes directly on the surface of the brain to test for sensory stimulation. His observation of fluctuating brain activity led to the conclusion of brain waves.In 1912, Ukrainian physiologist published the first animal EEG and the of the (dog). In 1914, and Jelenska-Macieszyna photographed EEG recordings of experimentally induced seizures.German physiologist and psychiatrist (1873–1941) recorded the first human EEG in 1924.
Expanding on work previously conducted on animals by Richard Caton and others, Berger also invented the electroencephalogram (giving the device its name), an invention described 'as one of the most surprising, remarkable, and momentous developments in the history of clinical neurology'. His discoveries were first confirmed by British scientists and B. Matthews in 1934 and developed by them.In 1934, Fisher and Lowenback first demonstrated epileptiform spikes.
In 1935, Gibbs, Davis and Lennox described inter spike waves and the three cycles/s pattern of clinical, which began the field of clinical electroencephalography. Subsequently, in 1936 Gibbs and Jasper reported the interictal spike as the focal signature of epilepsy. The same year, the first EEG laboratory opened at Massachusetts General Hospital.Franklin Offner (1911–1999), professor of biophysics at developed a prototype of the EEG that incorporated a piezoelectric inkwriter called a (the whole device was typically known as the ).In 1947, The American EEG Society was founded and the first International EEG congress was held. In 1953 Aserinsky and Kleitman described REM sleep.In the 1950s, developed an adjunct to EEG called, which allowed for the mapping of electrical activity across the surface of the brain.
This enjoyed a brief period of popularity in the 1980s and seemed especially promising for psychiatry. It was never accepted by neurologists and remains primarily a research tool. Chuck Kayser with electroencephalograph electrodes and a signal conditioner for use in, 1965An electroencephalograph system manufactured by Beckman Instruments was used on at least one of the manned spaceflights (1965-1966) to monitor the brain waves of astronauts on the flight. It was one of many Beckman Instruments specialized for and used by NASA.In 1988, report was given by Stevo Bozinovski, Mihail Sestakov, and Liljana Bozinovska on EEG control of a physical object, a robot.In October 2018, scientists connected the brains of three people to experiment with the process of thoughts sharing. Five groups of three people participated in the experiment using EEG.
The success rate of the experiment was 81%. Medical use. An EEG recording setupEEG is one of the main diagnostic tests for epilepsy. A routine clinical EEG recording typically lasts 20–30 minutes (plus preparation time). It is a test that detects electrical activity in the brain using small, metal discs (electrodes) attached to your scalp.
Routinely, EEG is used in clinical circumstances to determine changes in brain activity that might be useful in diagnosing brain disorders, especially epilepsy or another seizure disorder. Computer electroencephalograph Neurovisor-BMM 40In conventional scalp EEG, the recording is obtained by placing on the scalp with a conductive gel or paste, usually after preparing the scalp area by light to reduce due to dead skin cells. Many systems typically use electrodes, each of which is attached to an individual wire. Some systems use caps or nets into which electrodes are embedded; this is particularly common when high-density arrays of electrodes are needed.Electrode locations and names are specified by the for most clinical and research applications (except when high-density arrays are used). This system ensures that the naming of electrodes is consistent across laboratories.
In most clinical applications, 19 recording electrodes (plus ground and system reference) are used. A smaller number of electrodes are typically used when recording EEG from. Additional electrodes can be added to the standard set-up when a clinical or research application demands increased spatial resolution for a particular area of the brain. High-density arrays (typically via cap or net) can contain up to 256 electrodes more-or-less evenly spaced around the scalp.Each electrode is connected to one input of a (one amplifier per pair of electrodes); a common system reference electrode is connected to the other input of each differential amplifier.
These amplifiers amplify the voltage between the active electrode and the reference (typically 1,000–100,000 times, or 60–100 of voltage gain). In analog EEG, the signal is then filtered (next paragraph), and the EEG signal is output as the deflection of pens as paper passes underneath.
Most EEG systems these days, however, are digital, and the amplified signal is digitized via an, after being passed through an. Analog-to-digital sampling typically occurs at 256–512 Hz in clinical scalp EEG; sampling rates of up to 20 kHz are used in some research applications.During the recording, a series of activation procedures may be used. These procedures may induce normal or abnormal EEG activity that might not otherwise be seen. These procedures include hyperventilation, photic stimulation (with a strobe light), eye closure, mental activity, sleep and sleep deprivation.
During (inpatient) epilepsy monitoring, a patient's typical seizure medications may be withdrawn.The digital EEG signal is stored electronically and can be filtered for display. Typical settings for the and a are 0.5–1 and 35–70 Hz respectively. The high-pass filter typically filters out slow artifact, such as signals and movement artifact, whereas the low-pass filter filters out high-frequency artifacts, such as signals. An additional is typically used to remove artifact caused by electrical power lines (60 Hz in the United States and 50 Hz in many other countries).The EEG signals can be captured with opensource hardware such as and the signal can be processed by freely available EEG software such as or the.As part of an evaluation for epilepsy surgery, it may be necessary to insert electrodes near the surface of the brain, under the surface of the. This is accomplished via burr hole. This is referred to variously as, 'intracranial EEG (I-EEG)' or 'subdural EEG (SD-EEG)'.
Depth electrodes may also be placed into brain structures, such as the or, structures, which are common epileptic foci and may not be 'seen' clearly by scalp EEG. The electrocorticographic signal is processed in the same manner as digital scalp EEG (above), with a couple of caveats. ECoG is typically recorded at higher sampling rates than scalp EEG because of the requirements of —the subdural signal is composed of a higher predominance of higher frequency components. Also, many of the artifacts that affect scalp EEG do not impact ECoG, and therefore display filtering is often not needed.A typical adult human EEG signal is about 10 µV to 100 µV in amplitude when measured from the scalp and is about 10–20 mV when measured from subdural electrodes.Since an EEG voltage signal represents a difference between the voltages at two electrodes, the display of the EEG for the reading encephalographer may be set up in one of several ways. The representation of the EEG channels is referred to as a montage.
Sequential montage Each channel (i.e., waveform) represents the difference between two adjacent electrodes. The entire montage consists of a series of these channels. For example, the channel 'Fp1-F3' represents the difference in voltage between the Fp1 electrode and the F3 electrode. The next channel in the montage, 'F3-C3', represents the voltage difference between F3 and C3, and so on through the entire array of electrodes. Referential montage Each channel represents the difference between a certain electrode and a designated reference electrode. There is no standard position for this reference; it is, however, at a different position than the 'recording' electrodes. Midline positions are often used because they do not amplify the signal in one hemisphere vs.
The other, such as Cz, Oz, Pz etc. As online reference. The other popular offline references are:. REST reference: which is an offline computational reference at infinity where the potential is zero.
REST (reference electrode standardization technique) takes the equivalent sources inside the brain of any a set of scalp recordings as springboard to link the actual recordings with any an online or offline( average, linked ears etc.) non-zero reference to the new recordings with infinity zero as the standardized reference. A free software can be found at (Dong L, Li F, Liu Q, Wen X, Lai Y, Xu P and Yao D (2017) MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG. Doi: 10.3389/fnins.2017.00601), and for more details and its performance, pls ref to the original paper (Yao, D. A method to standardize a reference of scalp EEG recordings to a point at infinity. Doi: 10.1088/0967-3334/22/4/305). 'linked ears': which is a physical or mathematical average of electrodes attached to both earlobes or.Average reference montage The outputs of all of the amplifiers are summed and averaged, and this averaged signal is used as the common reference for each channel.
Laplacian montage Each channel represents the difference between an electrode and a weighted average of the surrounding electrodes.When analog (paper) EEGs are used, the technologist switches between montages during the recording in order to highlight or better characterize certain features of the EEG. With digital EEG, all signals are typically digitized and stored in a particular (usually referential) montage; since any montage can be constructed mathematically from any other, the EEG can be viewed by the electroencephalographer in any display montage that is desired.The EEG is read by a or (depending on local custom and law regarding ), optimally one who has specific training in the interpretation of EEGs for clinical purposes. This is done by visual inspection of the waveforms, called graphoelements. The use of computer signal processing of the EEG—so-called —is somewhat controversial when used for clinical purposes (although there are many research uses).Dry EEG electrodes In the early 1990s Babak Taheri, at demonstrated the first single and also multichannel dry active electrode arrays using micro-machining. The single channel dry EEG electrode construction and results were published in 1994. The arrayed electrode was also demonstrated to perform well compared to / electrodes. The device consisted of four sites of sensors with integrated electronics to reduce noise.
The advantages of such electrodes are: (1) no electrolyte used, (2) no skin preparation, (3) significantly reduced sensor size, and (4) compatibility with EEG monitoring systems. The active electrode array is an integrated system made of an array of capacitive sensors with local integrated circuitry housed in a package with batteries to power the circuitry. This level of integration was required to achieve the functional performance obtained by the electrode. The electrode was tested on an electrical test bench and on human subjects in four modalities of EEG activity, namely: (1) spontaneous EEG, (2) sensory event-related potentials, (3) brain stem potentials, and (4) cognitive event-related potentials.
The performance of the dry electrode compared favorably with that of the standard wet electrodes in terms of skin preparation, no gel requirements (dry), and higher signal-to-noise ratio.In 1999 researchers at, in, led by Hunter Peckham, used 64-electrode EEG skullcap to return limited hand movements to Jim Jatich. As Jatich concentrated on simple but opposite concepts like up and down, his beta-rhythm EEG output was analysed using software to identify patterns in the noise. A basic pattern was identified and used to control a switch: Above average activity was set to on, below average off. As well as enabling Jatich to control a computer cursor the signals were also used to drive the nerve controllers embedded in his hands, restoring some movement.In 2018, a functional dry electrode composed of a polydimethylsiloxane filled with conductive carbon was reported. This research was conducted at the.
EEG technology often involves applying a gel to the scalp which facilitates strong signal-to-noise ratio. This results in more reproducible and reliable experimental results.
Since patients dislike having their hair filled with gel, and the lengthy setup requires trained staff on hand, utilizing EEG outside the laboratory setting can be difficult. Additionally, it has been observed that wet electrode sensors’ performance reduces after a span of hours. Therefore, research has been directed to developing dry and semi-dry EEG bioelectronic interfaces.Dry electrode signals depend upon mechanical contact. Therefore, it can be difficult getting a usable signal because of impedance between the skin and the electrode. Some EEG systems attempt to circumvent this issue by applying a saline solution. Others have a semi dry nature and release small amounts of the gel upon contact with the scalp. Another solution uses spring loaded pin setups.
These may be uncomfortable. They may also be dangerous if they were used in a situation where a patient could bump their head since they could become lodged after an impact trauma incident.ARL also developed a visualization tool, Customizable Lighting Interface for the Visualization of EEGs or CLIVE, which showed how well two brains are synchronized. Limitations EEG has several limitations. Most important is its poor spatial resolution. EEG is most sensitive to a particular set of post-synaptic potentials: those generated in superficial layers of the cortex, on the crests of directly abutting the skull and radial to the skull. Dendrites, which are deeper in the cortex, inside, in midline or deep structures (such as the or ), or producing currents that are tangential to the skull, have far less contribution to the EEG signal.EEG recordings do not directly capture axonal. An action potential can be accurately represented as a current, meaning that the resulting field decreases more rapidly than the ones produced by the current dipole of post-synaptic potentials.
In addition, since EEGs represent averages of thousands of neurons, a large population of cells in synchronous activity is necessary to cause a significant deflection on the recordings. Action potentials are very fast and, as a consequence, the chances of field summation are slim. However, as a typically longer dendritic current dipole, can be picked up by EEG electrodes and is a reliable indication of the occurrence of neural output.Not only do EEGs capture dendritic currents almost exclusively as opposed to axonal currents, they also show a preference for activity on populations of parallel dendrites and transmitting current in the same direction at the same time. Of cortical layers II/III and V extend apical dendrites to layer I.
Currents moving up or down these processes underlie most of the signals produced by electroencephalography.Therefore, EEG provides information with a large bias to select neuron types, and generally should not be used to make claims about global brain activity. The, and skull 'smear' the EEG signal, obscuring its intracranial source.It is mathematically impossible to reconstruct a unique intracranial current source for a given EEG signal, as some currents produce potentials that cancel each other out. This is referred to as the. However, much work has been done to produce remarkably good estimates of, at least, a localized that represents the recorded currents. EEG vs fMRI, fNIRS and PET EEG has several strong points as a tool for exploring brain activity. EEGs can detect changes over milliseconds, which is excellent considering an takes approximately 0.5–130 milliseconds to propagate across a single neuron, depending on the type of neuron. Other methods of looking at brain activity, such as and have time resolution between seconds and minutes.
EEG measures the brain's electrical activity directly, while other methods record changes in blood flow (e.g., ) or metabolic activity (e.g., ), which are indirect markers of brain electrical activity. EEG can be used simultaneously with so that high-temporal-resolution data can be recorded at the same time as high-spatial-resolution data, however, since the data derived from each occurs over a different time course, the data sets do not necessarily represent exactly the same brain activity. There are technical difficulties associated with combining these two modalities, including the need to remove the MRI gradient artifact present during MRI acquisition and the ballistocardiographic artifact (resulting from the pulsatile motion of blood and tissue) from the EEG. Furthermore, currents can be induced in moving EEG electrode wires due to the magnetic field of the MRI.EEG can be used simultaneously with without major technical difficulties. There is no influence of these modalities on each other and a combined measurement can give useful information about electrical activity as well as local hemodynamics.EEG vs MEG EEG reflects correlated synaptic activity caused by of cortical. The ionic currents involved in the generation of fast may not contribute greatly to the averaged representing the EEG.
More specifically, the scalp electrical potentials that produce EEG are generally thought to be caused by the extracellular ionic currents caused by electrical activity, whereas the fields producing signals are associated with intracellular ionic currents.EEG can be recorded at the same time as so that data from these complementary high-time-resolution techniques can be combined.Studies on numerical modeling of EEG and MEG have also been done. Normal activity. Common artifacts in human EEG. 1: Electrooculographic artifact caused by the excitation of eyeball's muscles (related to blinking, for example). Big-amplitude, slow, positive wave prominent in frontal electrodes. 2: Electrode's artifact caused by bad contact (and thus bigger impedance) between P3 electrode and skin.
3: Swallowing artifact. 4: Common reference electrode's artifact caused by bad contact between reference electrode and skin. Huge wave similar in all channels.The EEG is typically described in terms of (1) and (2) transients. The rhythmic activity is divided into bands by frequency. To some degree, these frequency bands are a matter of nomenclature (i.e., any rhythmic activity between 8–12 Hz can be described as 'alpha'), but these designations arose because rhythmic activity within a certain frequency range was noted to have a certain distribution over the scalp or a certain biological significance. Frequency bands are usually extracted using spectral methods (for instance Welch) as implemented for instance in freely available EEG software such as or the.Computational processing of the EEG is often named (qEEG).Most of the cerebral signal observed in the scalp EEG falls in the range of 1–20 Hz (activity below or above this range is likely to be artifactual, under standard clinical recording techniques). Waveforms are subdivided into bandwidths known as alpha, beta, theta, and delta to signify the majority of the EEG used in clinical practice.
is the frequency range up to 4 Hz. It tends to be the highest in amplitude and the slowest waves. It is seen normally in adults in. It is also seen normally in babies. It may occur focally with subcortical lesions and in general distribution with diffuse lesions, metabolic encephalopathy hydrocephalus or deep midline lesions.
It is usually most prominent frontally in adults (e.g. FIRDA – frontal intermittent rhythmic delta) and posteriorly in children (e.g. OIRDA – occipital intermittent rhythmic delta).
is the frequency range from 4 Hz to 7 Hz. Theta is seen normally in young children. It may be seen in drowsiness or arousal in older children and adults; it can also be seen in. Excess theta for age represents abnormal activity. It can be seen as a focal disturbance in focal subcortical lesions; it can be seen in generalized distribution in diffuse disorder or metabolic encephalopathy or deep midline disorders or some instances of hydrocephalus. On the contrary this range has been associated with reports of relaxed, meditative, and creative states.
is the frequency range from 7 to 13 Hz. Named the first rhythmic EEG activity he observed the 'alpha wave'. This was the 'posterior basic rhythm' (also called the 'posterior dominant rhythm' or the 'posterior alpha rhythm'), seen in the posterior regions of the head on both sides, higher in amplitude on the dominant side. It emerges with closing of the eyes and with relaxation, and attenuates with eye opening or mental exertion. The posterior basic rhythm is actually slower than 8 Hz in young children (therefore technically in the theta range). is the frequency range from 14 Hz to about 30 Hz. It is seen usually on both sides in symmetrical distribution and is most evident frontally.
Beta activity is closely linked to motor behavior and is generally attenuated during active movements. Low-amplitude beta with multiple and varying frequencies is often associated with active, busy or anxious thinking and active concentration. Rhythmic beta with a dominant set of frequencies is associated with various pathologies, such as, and drug effects, especially.
It may be absent or reduced in areas of cortical damage. It is the dominant rhythm in patients who are alert or anxious or who have their eyes open. is the frequency range approximately 30–100 Hz. Gamma rhythms are thought to represent binding of different populations of neurons together into a network for the purpose of carrying out a certain cognitive or motor function.
range is 8–13 Hz and partly overlaps with other frequencies. It reflects the synchronous firing of motor neurons in rest state. Mu suppression is thought to reflect motor mirror neuron systems, because when an action is observed, the pattern extinguishes, possibly because the normal and mirror neuronal systems 'go out of sync' and interfere with one other.' Ultra-slow' or 'near-' activity is recorded using DC amplifiers in some research contexts. It is not typically recorded in a clinical context because the signal at these frequencies is susceptible to a number of artifacts.Some features of the EEG are transient rather than rhythmic.
Spikes and sharp waves may represent seizure activity or activity in individuals with epilepsy or a predisposition toward epilepsy. Other transient features are normal: vertex waves and sleep spindles are seen in normal sleep.Note that there are types of activity that are statistically uncommon, but not associated with dysfunction or disease. These are often referred to as 'normal variants'. The mu rhythm is an example of a normal variant.The normal electroencephalogram (EEG) varies by age. The and neonatal EEG is quite different from the adult EEG. Fetuses in the third trimester and newborns display two common brain activity patterns: 'discontinuous' and 'trace alternant.'
'Discontinuous' electrical activity refers to sharp bursts of electrical activity followed by low frequency waves. 'Trace alternant' electrical activity describes sharp bursts followed by short high amplitude intervals and usually indicates quiet sleep in newborns. The EEG in childhood generally has slower frequency oscillations than the adult EEG.The normal EEG also varies depending on state. The EEG is used along with other measurements (, ) to define in.
Stage I sleep (equivalent to drowsiness in some systems) appears on the EEG as drop-out of the posterior basic rhythm. There can be an increase in theta frequencies. Santamaria and Chiappa cataloged a number of the variety of patterns associated with drowsiness. Stage II sleep is characterized by sleep spindles – transient runs of rhythmic activity in the 12–14 Hz range (sometimes referred to as the 'sigma' band) that have a frontal-central maximum. Most of the activity in Stage II is in the 3–6 Hz range. Stage III and IV sleep are defined by the presence of delta frequencies and are often referred to collectively as 'slow-wave sleep'.
Stages I–IV comprise non-REM (or 'NREM') sleep. The EEG in REM (rapid eye movement) sleep appears somewhat similar to the awake EEG.EEG under general anesthesia depends on the type of anesthetic employed. With halogenated anesthetics, such as or intravenous agents, such as, a rapid (alpha or low beta), nonreactive EEG pattern is seen over most of the scalp, especially anteriorly; in some older terminology this was known as a WAR (widespread anterior rapid) pattern, contrasted with a WAIS (widespread slow) pattern associated with high doses of.
Anesthetic effects on EEG signals are beginning to be understood at the level of drug actions on different kinds of synapses and the circuits that allow synchronized neuronal activity (see: ).Artifacts Biological artifacts. Main types of artifacts in human EEGElectrical signals detected along the scalp by an EEG, but are of non-cerebral origin are called. EEG data is almost always contaminated by such artifacts. The amplitude of artifacts can be quite large relative to the size of amplitude of the cortical signals of interest. This is one of the reasons why it takes considerable experience to correctly interpret EEGs clinically. Some of the most common types of biological artifacts include:.
Eye-induced artifacts (includes eye blinks, eye movements and extra-ocular muscle activity). (cardiac) artifacts. (muscle activation)-induced artifacts.
Glossokinetic artifactsThe most prominent eye-induced artifacts are caused by the potential difference between the and, which is quite large compared to cerebral potentials. When the eyes and eyelids are completely still, this corneo-retinal dipole does not affect EEG.
However, blinks occur several times per minute, the eyes movements occur several times per second. Eyelid movements, occurring mostly during blinking or vertical eye movements, elicit a large potential seen mostly in the difference between the (EOG) channels above and below the eyes. An established explanation of this potential regards the eyelids as sliding electrodes that short-circuit the positively charged cornea to the extra-ocular skin. Rotation of the eyeballs, and consequently of the corneo-retinal dipole, increases the potential in electrodes towards which the eyes are rotated, and decrease the potentials in the opposing electrodes.
Eye movements called also generate transient potentials, known as saccadic spike potentials (SPs). The spectrum of these SPs overlaps the gamma-band (see ), and seriously confounds analysis of induced gamma-band responses, requiring tailored artifact correction approaches.
Purposeful or reflexive eye blinking also generates potentials, but more importantly there is reflexive movement of the eyeball during blinking that gives a characteristic artifactual appearance of the EEG (see ).Eyelid fluttering artifacts of a characteristic type were previously called Kappa rhythm (or Kappa waves). It is usually seen in the prefrontal leads, that is, just over the eyes. Sometimes they are seen with mental activity. They are usually in the Theta (4–7 Hz) or Alpha (7–14 Hz) range. They were named because they were believed to originate from the brain.
Later study revealed they were generated by rapid fluttering of the eyelids, sometimes so minute that it was difficult to see. They are in fact noise in the EEG reading, and should not technically be called a rhythm or wave. Therefore, current usage in electroencephalography refers to the phenomenon as an eyelid fluttering artifact, rather than a Kappa rhythm (or wave).Some of these artifacts can be useful in various applications. The EOG signals, for instance, can be used to detect and, which are very important in, and is also in conventional EEG for assessing possible changes in alertness, drowsiness or sleep.artifacts are quite common and can be mistaken for spike activity.
Because of this, modern EEG acquisition commonly includes a one-channel from the extremities. This also allows the EEG to identify that are an important to or other episodic/attack disorders.Glossokinetic artifacts are caused by the potential difference between the base and the tip of the tongue.
Minor tongue movements can contaminate the EEG, especially in and disorders.Environmental artifacts In addition to artifacts generated by the body, many artifacts originate from outside the body. Movement by the patient, or even just settling of the electrodes, may cause electrode pops, spikes originating from a momentary change in the of a given electrode. Poor of the EEG electrodes can cause significant 50 or 60 Hz artifact, depending on the local power system's. A third source of possible interference can be the presence of an; such devices can cause rhythmic, fast, low-voltage bursts, which may be confused for spikes.Motion artifacts introduce signal noise that can mask the neural signal of interest. Therefore, effective signal noise processing measures were of great interest in the scientific community.An EEG equipped phantom head can be placed on a motion platform and moved in a sinusoidal fashion.
This contraption enabled researchers to study the effectiveness of motion artifact removal algorithms. Using the same model of phantom head and motion platform, it was determined that cable sway was a major attributor to motion artifacts. However, increasing the surface area of the electrode had a small but significant effect on reducing the artifact. This research was sponsored by the as a part of the.Artifact correction Recently, (ICA) techniques have been used to correct or remove EEG contaminants.
These techniques attempt to 'unmix' the EEG signals into some number of underlying components. There are many source separation algorithms, often assuming various behaviors or natures of EEG. Regardless, the principle behind any particular method usually allow 'remixing' only those components that would result in 'clean' EEG by nullifying (zeroing) the weight of unwanted components. Fully automated artifact rejection methods, which use ICA, have also been developed.In the last few years, by comparing data from paralysed and unparalysed subjects, EEG contamination by muscle has been shown to be far more prevalent than had previously been realized, particularly in the gamma range above 20 Hz.
However, Surface has been shown to be effective in eliminating muscle artefact, particularly for central electrodes, which are further from the strongest contaminants. The combination of Surface Laplacian with automated techniques for removing muscle components using ICA proved particularly effective in a follow up study. Abnormal activity Abnormal activity can broadly be separated into and non-epileptiform activity. It can also be separated into focal or diffuse.Focal epileptiform discharges represent fast, synchronous potentials in a large number of neurons in a somewhat discrete area of the brain. These can occur as interictal activity, between seizures, and represent an area of cortical irritability that may be predisposed to producing epileptic seizures.
Interictal discharges are not wholly reliable for determining whether a patient has epilepsy nor where his/her seizure might originate. (See.)Generalized epileptiform discharges often have an anterior maximum, but these are seen synchronously throughout the entire brain. They are strongly suggestive of a generalized epilepsy.Focal non-epileptiform abnormal activity may occur over areas of the brain where there is focal damage of the cortex. It often consists of an increase in slow frequency rhythms and/or a loss of normal higher frequency rhythms. It may also appear as focal or unilateral decrease in amplitude of the EEG signal.Diffuse non-epileptiform abnormal activity may manifest as diffuse abnormally slow rhythms or bilateral slowing of normal rhythms, such as the PBR.Intracortical Encephalogram electrodes and sub-dural electrodes can be used in tandem to discriminate and discretize artifact from epileptiform and other severe neurological events.More advanced measures of abnormal EEG signals have also recently received attention as possible biomarkers for different disorders such as. Remote communication The United States Army Research Office budgeted $4 million in 2009 to researchers at the University of California, Irvine to develop EEG processing techniques to identify correlates of and intended direction to enable soldiers on the battlefield to communicate via computer-mediated reconstruction of team members' EEG signals, in the form of understandable signals such as words.
Eeg Visualization Software
EEG Diagnostics The (DoD) and (VA), and (ARL), collaborated on EEG diagnostics in order to detect (mTBI) in combat soldiers. Between 2000 and 2012 seventy-five percent of U.S. Military operations brain injuries were classified mTBI. In response, the pursued new technologies capable of rapid, accurate, non-invasive, and field-capable detection of mTBI to address this injury.Combat personnel often suffer PTSD and mTBI in correlation. Both conditions present with altered low-frequency brain wave oscillations. Altered brain waves from PTSD patients present with decreases in low-frequency oscillations, whereas, mTBI injuries are linked to increased low-frequency wave oscillations.
Effective EEG diagnostics can help doctors accurately identify conditions and appropriately treat injuries in order to mitigate long-term effects.Traditionally, clinical evaluation of EEGs involved visual inspection. Instead of a visual assessment of brain wave oscillation topography, quantitative electroencephalography (qEEG), computerized algorithmic methodologies, analyzes a specific region of the brain and transforms the data into a meaningful “power spectrum” of the area. Accurately differentiating between mTBI and PTSD can significantly increase positive recovery outcomes for patients especially since long-term changes in neural communication can persist after an initial mTBI incident. Economics Inexpensive EEG devices exist for the low-cost research and consumer markets. Recently, a few companies have miniaturized medical grade EEG technology to create versions accessible to the general public.
Some of these companies have built commercial EEG devices retailing for less than US$100. In 2004 OpenEEG released its ModularEEG as open source hardware. Compatible open source software includes a game for balancing a ball. In 2007 released the first affordable consumer based EEG along with the game NeuroBoy. This was also the first large scale EEG device to use dry sensor technology. In 2008 developed device for use in video games relying primarily on.
In 2008 the developer announced that it was partnering with NeuroSky to create a game, Judecca. In 2009 partnered with NeuroSky to release the, a game that used an EEG to steer a ball through an obstacle course. By far the best selling consumer based EEG to date. In 2009 Uncle Milton Industries partnered with NeuroSky to release the, a game designed to create the illusion of possessing.
In 2009 released the EPOC, a 14 channel EEG device. The EPOC is the first commercial BCI to not use dry sensor technology, requiring users to apply a saline solution to electrode pads (which need remoistening after an hour or two of use). In 2010, NeuroSky added a blink and electromyography function to the MindSet. In 2011, NeuroSky released the MindWave, an EEG device designed for educational purposes and games. The MindWave won the Guinness Book of World Records award for 'Heaviest machine moved using a brain control interface'. In 2012, a Japanese gadget project, released Necomimi: a headset with motorized cat ears.
Eeg Analysis Software
The headset is a NeuroSky MindWave unit with two motors on the headband where a cat's ears might be. Slipcovers shaped like cat ears sit over the motors so that as the device registers emotional states the ears move to relate.
For example, when relaxed, the ears fall to the sides and perk up when excited again. In 2014, OpenBCI released an eponymous brain-computer interface after a successful kickstarter campaign in 2013. The basic has 8 channels, expandable to 16, and supports EEG,. Psicologia social aroldo rodrigues pdf. The OpenBCI is based on the Texas Instruments ADS1299 and the Arduino or PIC microcontroller, and costs $399 for the basic version.
It uses standard metal cup electrodes and conductive paste. In 2015, released the smallest consumer BCI to date, the. This device functions as a dry sensor at a size no larger than a ear piece. In 2015, A Chinese-based company released and, a EEG wearable product providing 20 brain fitness enhancement Apps on and.Future research.