noise in the signal. simple filtering using a notch filter is commonly employed to reject components with a 50/60 hz frequency. however such simple filters are not an appropriate choice for dealing with all artifacts, as for some, their frequencies will overlap with the eeg frequencies. regression algorithms have a moderate computation cost and are simple. they represented the most popular correction method up until the mid-1990s when they were replaced by "blind source separation" type methods. regression algorithms work on the premise that all artifacts are comprised by one or more reference channels. subtracting these reference channels from the other contaminated channels, in either the time or frequency domain, by estimating the impact of the reference channels on the other channels, would correct the channels for the artifact. although the requirement of reference channels ultimately lead to this class of algorithm being replaced, they still represent the benchmark to which modern algorithms are evaluated against. blind source separation (bss) algorithms employed to remove artifacts include principal component analysis (pca) and independent component analysis (ica) and several algorithms in the this class have been successful at tackling most physiological artifacts. artifact removal on a single electrode uses a reference segment obtained just before the artifact starts. the method consists in transporting the wavelet cumulative coefficient of the artifact onto the cumulative one of the reference signal. this normalization transport smooths the signal, so that the replaced signal instead of the artifact has similar statistical properties as the reference. the method is called wavelet quantil normalization wqn and can be used in real-time to remove artifacts on eeg sedline monitor. this approach performs better than classical soft and hard thresholding. ocular artifacts ocular artifacts affect the eeg signal significantly. this is due to eye movements involving a change in electric fields surrounding the eyes, distorting the electric field over the scalp, and as eeg is recorded on the scalp, it therefore distorts the recorded signal. a difference of opinion exists among researchers, with some arguing ocular artifacts are, or may be reasonably described as a single generator, whilst others argue it is important to understand the potentially complicated mechanisms. three potential mechanisms have been proposed to explain the ocular artifact. the first is corneal retinal dipole movement which argues that an electric dipole is formed between the cornea and retina, as the former is positively and the latter negatively charged. when the eye moves, so does this dipole which impacts the electrical field over the scalp, this is the most standard view. the second mechanism is retinal dipole movement, which is similar to the first but differing in that it argues there is a potential difference, hence dipole across the retina with the cornea having little effect. the third mechanism is eyelid movement. it is known that there is a change in voltage around the eyes when the eyelid moves, even if the eyeball does not. it is thought that the eyelid can be described as a sliding potential source and that the impacting of blinking is different to eye movement on the recorded eeg. 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). the propagation of the ocular artifact is impacted by multiple factors including the properties of the subject's skull, neuronal tissues and skin but the signal may be approximated as being inversely proportional to the distance from the eyes squared. the electrooculogram (eog) consists of a series of electrodes measuring voltage changes close to the eye and is the most common tool for dealing with the eye movement artifact in the eeg signal. muscular artifacts another source of artifacts are various muscle movements across the body. this particular class of artifact is usually recorded by all electrodes on the scalp due to myogenic activity (increase or decrease of blood pressure). the origin of these artifacts have no single location and arises from functionally independent muscle groups, meaning the characteristics of the artifact are not constant. the observed patterns due to muscular artifacts will change depending on the subjects sex, the particular muscle tissue and its degree of contraction. the frequency range for muscular artifacts is wide and overlaps with every classic eeg rhythm. however most of the power is concentrated in the lower range of the observed frequencies of 20 to 300 hz making the gamma band particularly susceptible to muscular artifacts. some muscle artifacts may have activity with a frequency as low as 2 hz which and delta and theta bands may also be affected by muscle activity. muscular artifacts may impact sleep studies as unconscious bruxism (grinding of teeth) or snoring can seriously impact the quality of the recorded eeg. in addition the recordings made of epilepsy patients may be significantly impacted by the existence of muscular artifacts. cardiac artifacts the potential due to cardiac activity introduces electrocardiograph (ecg) errors in the eeg. artifacts arising due to cardiac activity may be removed with the help of an ecg reference signal. other physiological artifacts 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 parkinsonian and tremor 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 impedance of a given electrode. poor grounding of the eeg electrodes can cause significant 50 or 60 hz artifact, depending on the local power system's frequency. a third source of possible interference can be the presence of an iv drip; such devices can cause rhythmic, fast, low-voltage bursts, which may be confused for spikes. abnormal activity abnormal activity can broadly be separated into epileptiform 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 focal epilepsy.) 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 or white matter. 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 alzheimer's disease. remote communication systems for decoding imagined speech from eeg have applications such as in brain–computer interfaces. eeg diagnostics the department of defense (dod) and veteran's affairs (va), and u.s army research laboratory (arl), collaborated on eeg diagnostics in order to detect mild to moderate traumatic brain injury (mtbi) in combat soldiers. between 2000 and 2012, 75 percent of u.s. military operations brain injuries were classified mtbi. in response, the dod pursued new technologies capable of rapid, accurate, non-invasive, and field-capable detection of mtbi to address this injury. combat personnel often develop 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. another common measurement made from eeg data is that of complexity measures such as lempel-ziv complexity, fractal dimension, and spectral flatness, which are associated with particular pathologies or pathology stages. 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 neurosky 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 ocz technology developed device for use in video games relying primarily on electromyography. in 2008 the final fantasy developer square enix announced that it was partnering with neurosky to create a game, judecca. in 2009 mattel partnered with neurosky to release the mindflex, 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 star wars force trainer, a game designed to create the illusion of possessing the force. 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, neurowear, released necomimi: a headset with motorized cat ears. 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 open source brain-computer interface after a successful kickstarter campaign in 2013. the basic openbci has 8 channels, expandable to 16, and supports eeg, ekg, and emg. the openbci is based on the texas instruments ads1299 ic and the arduino or pic microcontroller, and costs $399 for the basic version. it uses standard metal cup electrodes and conductive paste. in 2015, mind solutions inc released the smallest consumer bci to date, the neurosync. this device functions as a dry sensor at a size no larger than a bluetooth ear piece. in 2015, a chinese-based company macrotellect released brainlink pro and brainlink lite, a consumer grade eeg wearable product providing 20 brain fitness enhancement apps on apple and android app stores. in 2021, bioserenity release the neuronaute and icecap a single-use disposable eeg headset that allows recording with equivalent quality to traditional cup electrodes. future research the eeg has been used for many purposes besides the conventional uses of clinical diagnosis and conventional cognitive neuroscience. an early use was during world war ii by the u.s. army air corps to screen out pilots in danger of having seizures; long-term eeg recordings in epilepsy