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2.1 BCI / EEGThe brain consists of billions of neurons. Communication between neurons ismanifested in electrical signals. Electroencephalography (EEG) measures thiselectrical activity along the scalp. This is a well established technique fromthe 1920s. EEG has a low spatial but a high temporal resolution which makes itideal for recording changes in brain activities in response to events.
A BCItakes brain activity - for example in the form of an EEG signal (which is thecase for all BCIs mentioned in this thesis) - as input. For example, Figure shows an EEG signal with visible alpha waves. Figure 2.1: EEG signal with alpha waves marked with black boxes.Brain activity is not the only source of electrical signals along thescalp. Muscle activation also relies on electrical signals, the measuring ofwhich is called electromyography (EMG). Eye movement furthermore dischargeselectricity due to the eyes dipole properties - measuring this signal is calledelectrooculography (EOG). In the context of measuring EEG, EMG and EOG aretypical noise artifacts.EEG is measured either with stand-alone electrodes or electrodes attached to acap.
Examples of high fidelity EEG BCIs are the gamma-2-cap from g.tec and Easy Cap from EASYCAP. Some caps can even have up to 256 electrodesmounted. Caps need mounting preparationswith gel to improve the conductivity between scalp and electrodes. We have triedout the gamma-2-cap during a BCI seminar in Aalborg 2013 (Figure). A hi-fi EEG based BCI cost around10-15.000 Euro and includes, for example, a cap with electrodes, cablesand an amplifier.The EEG data is usually processed and analyzed off line with tools like EEG-lab or FieldTrip which are open-source plug-ins to MATLAB.
2.1.1 Classic BCI applications and techniquesThere are different approaches to processing a raw EEG signal. Some of these andtheir typical applications are briefly covered below.Evoked Potentials correlates visual/auditory stimuli with EEG responses. When anevent of significance is perceived, the brain fires certain actionresponses.
One widely used response is the P300 which manifests itself as a peakin the EEG signal 300 ms after a stimulus - for example a flash of an image. Inthe intendiX P300 speller application fromg.tec different letters are flashed for user while the P300 action response isused to determine which letter the user wants to select.Motor imagery is another classic approach to BCI in which an imagined movementof a body part causes motor cortex activity which is detected by the BCI. Inthis way imagined movement can be used for example to control wheel chairs andother vehicles. This techniquehas been used in gaming as well, e.g. For trigger activation.
Motor imagery requires spatialization(localization) of brain activity especially within motor cortex. Thispresents a challenge for EEG based BCIs since they have a low spatialresolution.Classification of EEG signals are widely used within BCI applications.
Forexample, it has been used for unique identification of a person forauthentication purpose. Variousresearch groups uses classifications to predict epilepsy attacks. Others do patternmatching on walking motions for assisting in rehabilitation after strokes. This approach has also been used to classify:( i) emotions like joy and anger; and ( ii) human expressions like a happyfacial expression or a mental mood. (b) Single channel EEG after Fast Fourier transform (FFT) has been applied.Figure 2.3: Raw EEG and Fast Fourier transformed EEG.Frequency analysis is another technique for processing EEG data.Neurons are organized in networks and communication among them is always ongoingin oscillatory patterns. Frequency analysis estimates the power of eachfrequency component.
One common approach to frequency analysis is to apply FastFourier transform (FFT) - a simple example is plotted in Figure. When applying FFT we go from a time domaininto a frequency domain as can be seen on the x-axis values of the plots beforeand after FFT. Frequency analysis is often used in conjunction withother methods of analysis - for example to extract features for classification. It is also used stand-alone either forneurofeedback or in research aiming to correlate certain frequency patterns withsome condition or cognitive task. This is very typical within EEG researchexemplified by a study showing that '. High resting theta power in healthyolder adults is associated with better cognitive function'.Frequency analysis is interesting due to the correlation between frequencies andmental states.
A rough overview is lined up in Table. Brainwave TypeFrequency rangeMental states and conditionsDelta0.5Hz to 3.5HzDeep sleepTheta3.5Hz to 8HzFalling asleepAlpha8Hz to 12HzRelaxed awake state (dominant with eyes closed)Beta12Hz to 30HzMental activity, attention, concentrationMidrangeBeta16Hz to 20HzThinking, aware of self & surroundingsHigh Beta21Hz to 30HzAlertness, agitationGamma30Hz to 100HzReflects the mechanism of consciousnessFigure 2.4: Generalized frequency bandsThe hi-fi BCIs are getting mobile. This trend is exemplified by a mobile versionof the Easy Cap and helmets with built in EEG sensors for soldiers. Another branch of BCIs that have come far ingetting mobile are the consumer BCIs as described in the next section. 2.2 Consumer BCIsWithin recent years consumer BCIs have emerged and moved BCIs outside thelaboratories. An early consumer BCI was the Neural Impulse Actuator (NIA) released in 2008 featuring a three forehead sensorconfiguration and connectivity through a desktop box with cables. NIA wasintended primarily for gaming and cost around 100 USD (it is not in productionany longer).
Consumer headsets today typically offer additional sensors(accelerometer, gyroscope, etc) and wireless connectivity. An overview ofcurrent state consumer BCIs is presented in Table.
2.2.1 Emotiv EPOCEPOC has out of the box a desktop SDK and a set of tools aimed at gaming. Theclosed source SDK provides detection of emotions, expressions, cognitive statesand more (Figure ).There is also a research edition of the EPOC headset which can record rawEEG. It comes with the TestBench desktop application forrecording and viewing the raw EEG data. TestBench can process EEG intovarious frequency bands and the raw EEG data can be exported in an EDF-format(multichannel biological and physical signals) (Appendix ).Before using the EPOC headset, the user has to moist each of its 14 electrode ina saline solution and then attach each electrode to the headset. Thispreparation took us about 10-15 minutes when some routine was achieved.The EPOC has no SDK for mobile devices, but has been hacked for mobile usage inconjunction with the USB dongle - we return to this in Section.EPOC seems to be the consumer BCI that appears most frequently in researchpapers. An overview of its application within research is given below.The FlyingBuddy2 uses motor imagery to make it possible for a disabled personto steer a Drone with the future perspective of steering a wheel chair. A group in Spain uses the out of the box SDKclassified facial expression (based on EMG) such as open and close clinchcombined with EOG data to steer a tractor.
Again using SDK classifications, an emotionbased chat application has been build featuring avatars that changes theirexpression from angry to happy based on the emotional state of a person. In a recent M.Sc. Thesis the EPOC was used for abrain wave biometrics authentication system. The NeuroPhone project used a P300approach to make phone calls on a smart phone - however the EEG processing wasperformed on a laptop. Finally, EPOChas also been used in a human-robot interaction study where they used EEG toclassify human satisfaction of the interaction with a robot.EPOC has also been used by media researchers at the DanishBroadcasting Corporation (DR) as a supplemental tool to qualitative interviewsand questionnaires. Throughout the video screening of a TV Drama production,the screening participants' brain states were measured in terms of EPOC SDKvalues such as excitement, frustration and attention.
In aninterview with Harddisken (a DR radio program about technology), Jacob LyngWieland - in charge of the experimental usage of BCI during video screenings -reported that they had skipped using the EPOC headset because it was toocumbersome to use. 2.2.2 NeuroSky MindWave MobileNeuroSky MindWave Mobile (MindWave) offersdesktop and mobile SDKs (IOS and Android). The closed source SDK featuresfrequencies processing and analysis outputting values for the level of'attention' and 'meditation' (Figure ).
The SDK also provides informationabout eye blinks and a number of frequency bands which we previously have linedout in Figure. TheMindWave SDK outputs the following frequency bands: delta (0.5 - 2.75Hz), theta (3.5 - 6.75Hz),low-alpha (7.5 - 9.25Hz), high-alpha (10 - 11.75Hz), low-beta (13 - 16.75Hz),high-beta (18 - 29.75Hz), low-gamma (31 - 39.75Hz) and mid-gamma (41 - 49.75Hz).The headset is easy to use and the SDK includes a simple Bluetooth API thatseamlessly supports device connectivity.
Due to its connectivity options and SDKsignal processing, the MindWave Mobile requires little effort to embed in aprototype. This has been done, for example, in a recent paper by Marchesi.He uses MindWave in theBRAVO project to detect attention among school children in an e-learningsetting. If a child's attention level is under some threshold, it its reportedto the other children who are encouraged to offer their help. In another study, a research group usesMindWave to measureattention during an online game.
They specifically look at the attentionlevels provided by the SDK versus self reported attention levels among a group ofparticipants. They conclude that the self reports and the SDK values are correlated. Another paper uses the attention andmeditation SDK values to examine the stress levels among participants whileperforming various tasks. It concluded that theMindSet was able to measure an increase in stressinduced by the tasks performed (Stroop test, Tower of Hanoi).In the brain state - defined in termsof EEG frequency composition - of a test subject driving a car is measured bya predecessor to the MindWave.
Raw EEG data is recorded to a mobile phone viabluetooth and its frequency composition is analyzed offline.Interestingly, the results show a change in the brain wave frequency patternwhen the driver performed, for example, a phone call.Finally, in a M.Sc. Thesis, classification of the raw EEG data from the MindSetis used to control a snake-like game aimed at children.MindWave comes out of the box with a mobile application named BrainwaveVisualizer which let its user inspect the current levels of the 8 frequencybands supported by the SDK. The app also provides simple neurofeedback byletting its user control the flying height of a ball by the SDK 'meditation'value or the intensity of a flame by the SDK 'attention' value. The sameapproach to neurofeedback is used in the third party app Transcend by PersonalNeuro. During meditation the user can get a flower to grow by increasing the'meditation' SDK value. 2.2.3 TrueSense KitTrueSense Kit is the newest, cheapest, most portable headset.
It comes with OPIConsole, an open source desktop application for recording and viewing raw EEGdata and analyzing sleep, meditation etc. From recorded EEG. It also enables exporting data asEDF-files for further processing and analysis in other applications.
The OPIConsole also offers sleep analysis and yoga performance analysis (Figure, Appendix ). The TrueSense Kit sensor(s) canbe placed on various parts of the body for measuring blood flow, heart rate, bodytemperature and body movements.TrueSense Kit records either directly to an internal memory module or transmitdata over ZigBee radio to the OPI Console through a USB receiver. The sensorscan be combined in a multi sensor configuration attached various places on thehead or body.TrueSense Kit provides no immediate mobile device connectivity but the OPI Consoleapplication can likely be ported to Android since it is build with the QTframework. Another approach would be to build anative C Android module from the TrueSense Kit C SDK. Since few Androiddevices currently support ZigBee out of the box, this would require anexternal receiver board.TrueSense Kit is not yet covered in any papers despite its support for flexibleexperimental setups.
TrueSense Kit was warmly received by the quantified selfcommunity at the yearly QS conference in Amsterdam 2013. 2.2.4 Future headsetsNew consumer BCIs are about to arrive, for example Muse (as briefly mentioned in the Introduction Section ) and Emotiv INSIGHT. These new headsets have some characteristics incommon which seem to be representative for the new generation of consumer BCIs:. they support Bluetooth.
they use dry electrodes. they are discrete and comfortable to wearAn interesting fact is that both of these headbands arecrowdfunded. Muse raised 287,472 USD in 2012 from an unknown amount ofsupporters at Indiegogo. EPOC Insight hadpledged 1,643,117 USD by the end of September 2013 from nearly 5000 people onKickstarter. This trends an interest inlow cost consumer BCIs and exemplifies pretotyping by presenting and selling theproduct before it has actually been build.Most importantly, these new BCIs strengthen the possibility for neurofeedbackamong consumers in their daily settings. In the next section we focus on theneurofeedback concept.
2.3 NeurofeedbackWhen given real time feedback on its oscillations, the brain can learn tocontrol and change them. This is interesting since the brains oscillations aresignificantly correlated with brain functions and behavior as well as withpsychiatric diseases. Neurofeedbacktraining exploits this mechanism by providing feedback based on oscillationfrequencies correlated with some desirable function or behavior.The neurofeedback mechanism was discovered and developed in the 1960s, but thefirst controlled studies providing clinical evidence supporting neurofeedbacktraining effects were published in the 1980s. Since then, the efficacy of neurofeedback therapyhas been documented in several studies andneurofeedback is listed among the treatments with highest evidencesupport for certain conditions according to The American Academy of Pediatrics(AAP). Neurofeedback is routinely used intreatment of a number of conditions including Attention Deficit HyperactivityDisorder (ADHD), anxiety, epilepsy, and addictive disorders.Besides its clinical usage, a number of studies show that neurofeedback trainingcan increase cognitive performance. For example, it has been shown to increasesemantic working memory,focused attention, perceptual sensitivity and reaction time.
Neurofeedback training has also been showneffective by real-life behavioral measures - e.g. By increasing musicalperformance in a stressful context among conservatory students in a studydesigned to ensure ecological validity. 2.3.2 Stress and alpha feedback trainingAlpha feedback training is the subset of neurofeedback training forwhich the goal state of the feedback is defined in terms of the amountof alpha waves - thereby seeking to increase the alpha activity.Alpha activity is associated with a relaxed consciousness. Together with theta, alpha is the EEGfrequency band in which effects of meditation are most significant.
Alpha 'blocking' (i.e.,reduction) is associated with alertness. Thus, by increasing alpha levels, alphafeedback training has been shown - amongst other positive effects suchas increased cognitive performance - to reduce stress and anxiety.With a classification approach, EEG has been used to classify subjectsfrom either a chronically stressed or a control group with a successrate higher than 90%. Thistestifies to the manifestation of stress in EEG data.The dominant frequency within the alpha band - the alpha peak - and theamplitude of the alpha band varies between individuals. An alpha feedback trainingsystem can account for this by calibrating accordingto the individual alpha peak and the baseline amount of alpha.
This is,for example, the approach taken in the alpha feedback system presented in. The importance of givingfeedback on individually determined frequency bands is investigated in and concludes that' Neurofeedback trainingapplied in individual EEG frequency ranges was muchmore efficient than neurofeedback training of standardEEG frequency ranges'. 2.4 Related worksHaving explained current state of consumer EEG BCIs, the neurofeedback mechanismand how alpha feedback training can help to reduce stress, we now presentexisting systems and research within the consumer neurofeedback domain. There isonly a limited number of such systems and research for reasons already mentionedabove:. Neurofeedback therapy is expanding but not widely adopted yet. Consumer BCIs have only emerged within recent years. They are still maturing and notwidely adopted yet.This section present and discuss the commercially available systemsBrainball and BioZen and the research project SmartphoneBrainScanner2.
2.4.1 BrainballAccording to the researchers behind, Brainball '. Dwells in the realm betweenart and research, entertainment and science, method and object'. They present a game with a tangible userinterface in which two opponents sit on a chair separated by a table. A steelball lies between them.
The players wear specialized BCIsmounted on their foreheads and somewhat similar to the NIA system (see Section).The EEG signal is analyzed into its frequency components and the ballwill roll away from the most relaxed player (drawing on the correlation betweenalpha activity and relaxation). While playing, the players are able to see ascreen visualizing their EEG activity. The creators of Brainball interestinglyreports that playing the game leads to increased relaxation by measure of bothGalvanic Skin Response (GSR) and self reports. Brainball experienced a lot of attentionincluding honorary mention at Ars Electronica 2000 and 100+ appearances onTV. However, it remains a niche product within gaming and entertainment due tothe dependency on specialized hardware (BCI, ball, screen, etc). TheBrainball BCI system is commercially available through a Swedishcompany under the name Mindball (Figure ). 2.4.2 BioZenBioZen is a consumer biofeedback systemdeveloped by the National Center for Telehealth and Technology (T2) under the USDepartment of Defense.
The fact alone that this organization is behind abiofeedback system witnesses to the increasing adoptation of the biofeedback(here under neurofeedback) method. The system consists of an Android application in conjunction with one or more consumerbio-sensors. Several sensors are supported including heart rate, skintemperature, GSR and EEG sensors. For EEG measurements, the Neurosky MindWave(and some older Neurosky BCIs) are supported. The BioZen app uses processed datadelivered from the Neurosky SDK (Delta, Theta, Low Alpha, High Alpha, Low Beta,High Beta, Low Gamma, Mid Gamma, (e)Attention, (e)Meditation) and these valuescan form the basis for neurofeedback training. Relying on the Neurosky SDK forfrequency analysis, BioZen is bound to the limited set of frequency spectramentioned above.On the BioZen web page, T2 claims that ' BioZen is the first portable, low-costmethod for clinicians and patients to use biofeedback in and out of the clinic'and that ' BioZen takes many of the large medical sensors in a clinic and putsthem in the hands of anyone with a smart phone'.
In other words, it is promoted for clinical usage -a claim the authors of this thesis are very cautious about making on behalf ofAlphaTrainer (see Section ). (c) Save feedback session with a tag (meditation, breathing, entertainment orworking) and a note.Figure 2.8: Screenshots of the neurofeedback from the BioZen Android app usingthe MindWave BCI (Images courtesy of BioZen).The feedback consists of an image of a hill in which the background brightnessand the visibility of a foreground tree are the feedback variables. Thebackground is brighter when the chosen parameter (e.g. Some EEG power band) ishigher while the foreground tree is more visible when the chosen parameter ismore stable (see Figure ). 2.4.3 Smartphone Brain Scanner 2The Smartphone Brain Scanner is developed at the Technical University of Denmark(DTU).
The project aims at moving EEG research out of the laboratory by means oflow cost wireless BCIs and smart phone based real-time neuroimaging softwarewhich ' may transform neuroscience experimental paradigms'. The important notion here is that whileleaving the laboratory and using consumer interfaces, the focus is still onresearch.They are in principle headset agnostic and support the Easy Cap and EPOC (described in Section )BCIs.
The EPOC is both used in its standard configuration and in a modifiedconfiguration in which it is merged with hi-fi gel based electrodes. On thesoftware side, they use their Smartphone Brain Scanner (SBS2) open sourcesoftware framework including state of the art EEG signal processing such assource reconstruction, noise filtering and frequency analysis.
It is build on the QT C framework which allows compilation to the major desktop andmobile operating systems. However, it is not trivial to embed a QT module insideanother native applications e.g.
On the Android platform. Wireless connection tothe EPOC BCI goes via an USB dongle and requires an Android phone to be rootedto function, the platform does not provide an easy way of interfacing with BCIsvia bluetooth. Furthermore it requires the research edition of the EPOC.To validate the design of the Smartphone Brain Scanner, the research team behindhas build 3 brain imaging applications including an alpha trainingapplication.
Again, the focus is on research - specifically, the interfaceparameters of neurofeedback training are investigated. The efficacy of twodifferent feedbacks were compared in a controlled study by measuring increase inalpha amplitudes with each interface during a week of intensive training. Onefeedback show a square changing colors between blue over gray to red for whichred represents high alpha. In another interface, high alpha amplitudes manifestsitself in the creation of small boxes and the color of the boxes created. Bykeeping the created boxes visible during the 5 minute training period, theinterface reveals performance history thus ' allowing the user to easily comparemethods for increasing the amplitudes' (Figure ).
The training effectmeasured by comparing baselines revealed only a statistic significant increasein alpha for the box changing colors while the alpha levels during training weresignificantly higher using the square creation interface.The conclusions especially relevant to this thesis are that:. Alpha feedback training is feasible in a mobile setup. Alpha levels during training (effect of feedback) is not necessarilycorrelated with a general increase in alpha levels (effect of training). 2.5 Sum up of background and related systemsTable lists neurofeedback systemswhich are either commercially available or use a consumer BCI.These systems have been chosen because theyoutline the current state of systems in the domain of AlphaTrainer.The parameters highlighted in the table expressparameters desirable or necessary for a consumer neurofeedback system.No existing system includes all parameters. For example,no consumer available system includes the ability to give feedback on individuallyadapted frequency bands which is important for the effectiveness ofthe feedback training (see Section ).This 'gap' among current neurofeedback systems is our motivationfor designing and buildingAlphaTrainer as discussed in the following chapters.
Posted byonFebruary 21st, 2016Tagged,These are exciting times for citizen neuroscientists. In the last few years, all kinds of new EEG systems have appeared.
When we first started looking into low-cost EEG hardware, we only found a handful of options — the OpenEEG project, the Emotiv EPOC, and Neurosky’s MindWave. Now, it’s hard to keep track of all the hardware to choose from, and harder still to decide which system is best for a particular use. The state of the art, obviously.Inspired by a long discussion of combinations over on, I decided to collect all the sub-$1,000 EEG hardware I could find into one post. Contents.DisclaimerAside from the OpenBCI and Emotiv EPOC, I have not personally tested any of these systems. This post should not be considered an endorsement, merely a list of some of the available options, some of which I wasn't aware of until recently.The list is roughly ordered by my personal assessment of the device's likely usefulness to readers, weighted by preference for open source, tinkerer-friendly designs and helpful, active user communities.
Comments regarding any of these devices or others that I might have missed are most welcome.OpenBCI: The Open Source Brain-computer Interface for Makers OpenBCI BoardThe is an open-source biosignals acquisition board that can handle EEG, EMG, and ECG signals with low noise and good sample rate.The OpenBCI’s learning curve is steeper than that of many other devices in this list, but it is also more flexible and powerful. Sony dvd architect pro 6.0 237 crack serial crack- funcionando de. The OpenBCI’s 100% open-source hardware and software invites tinkering, and there is an active online user community to share ideas and help out newcomers.The original OpenBCI has 8 channels and costs $499.99, but can be expanded to 16 channels with a Daisy Chain Module that brings the total cost to $899.99. It ships with gold cup electrodes and 10–20 conductive paste, as well as an adapter cable for use with “touch-proof” electrodes; it is also compatible with dry / active electrodes.This month OpenBCI wrapped up a second Kickstarter Campaign for a cheaper board with fewer channels, and a 3d-printable dry-electrode headset: OpenBCI Ganglion: Biosensing for Everybody OpenBCI Ganglion (prototype)The OpenBCI Ganglion has 4 channels and costs $99. It ships with the same gold-cup electrodes and 10–20 paste as the original OpenBCI.
It also has many of the same features — same form-factor, same software, and a micro SD card slot for logging data — but the Ganglion uses a Simblee bluetooth module rather than a Gazelle module, has half as many channels, and is less than a quarter the price.The Simblee bluetooth module will allow the Ganglion to stream data directly to a smartphone over BLE. Ultracortex: The open-source 3D printed EEG headset OpenBCI UltracortexThe Ultracortex is an open-source, 3D printed headset that holds EEG electrodes at configurable 10–20 system locations. The Ultracortex is compatible with the original OpenBCI as well as the OpenBCI Ganglion, and could probably be used with other EEG systems as well.The Ultracortex IV can be bought fully assembled for $599.99.
An unassembled Ultracortex kit is available for $399, and a print-it-yourself version for $299. You can also build your own Ultracortex from scratch much more inexpensively if you have a 3D printer, plenty of patience, and are willing to source the parts yourself.Further reading:. LOL.OpenEEG: Low-Cost, Open-Source, DIY EEG Signal Acquisition Hardware OpenEEG “Modular EEG” Analog Amplifier Board (photo credit: )The (it’s not a commercial company, but a group of enthusiasts) has released plans for several DIY EEG acquisition boards.
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They are all open-source hardware, and are compatible with a number of open-source software suites including OpenViBE, BrainBay, BioEra,. The most popular OpenEEG board at this point is the ModularEEG.The cost of the OpenEEG varies, because it is a DIY project, but assembled boards can be bought from Omilex for $60–110. According to OpenEEG’s website, a complete ModularEEG system, with electrodes and all, typically costs $200–400. The ModularEEG is a two-channel system, and is compatible with wide range of electrodes.Further reading:.Muse: The Brain-sensing Headband Muse HeadsetInteraxon’s is an easy-to-use brain-sensing headband that has apps for concentration and meditation training. It sends data over bluetooth and is compatible with recent versions of iOS, Android, Mac OS, Windows, and Ubuntu Linux.The Muse headband costs $299, has 4 channels — two on the forehead and two on the back of the head at 10–20 system locations AF3, AF4, TP9, and TP10. The reference electrode is at AFz.Though not open source, Muse does offer an open SDK that allows access to raw data as well as data that has been processed to some extent on the headset itself.
This, plus its user-friendly headband design (with low-fuss dry electrodes that avoid hairy regions) has made it a favorite among hackers and members of the art-tech avant garde.Further reading:.Neurosky MindWave: Affordable, hackable EEG headset Neurosky MindWave HeadsetThe Mindwave is low-cost consumer EEG headset that comes with a wide range of apps for meditation and concentration. The Mindwave uses a 2.4Gz RF link to send EEG data to Windows or Mac apps; the Mindwave Mobile uses a Bluetooth link to send EEG data to iOS or Android apps. The raw EEG data is unencrypted, and the MindWave also does some processing onboard and sends computed data, including:. Amplitude in each EEG band (Delta, Theta, Alpha, Beta, and Gamma). Output from NeuroSky proprietary eSense meters for “Attention” and “Meditation”. EEG/ECG signal quality data.The NeuroSky MindWave costs $79–99 and records 1 channel of EEG data using a dry passive electrode on the forehead (FP1) and a reference electrode clipped onto the left earlobe. The MindWave uses a 12bit ADC; the data sample rate is 512Hz.Further reading:.Emotiv: Dry and Wet electrode Gaming Headsetsmakes two reasonably affordable consumer gaming headsets, the Emotiv EPOC and the Emotiv Insight.
Emotiv EPOC/EPOC+ Emotiv EPOC (14 channel saline electrode gaming headset)The (launched 2009) sells for $399, and the EPOC+ (launched in 2015) sells for $499, but the data from the headset is encrypted, and you are not allowed you to access your raw EEG data without buying the $799 Developer SDK. The EPOC has 14 wet electrodes that use saline soaked felt pads, and two reference electrodes. It transmits encrypted EEG data over Bluetooth to a USB dongle. The Analog-Digital converter in the EPOC has 16 bit resolution.Shortly after the EPOC was launched, and Emotiv's Tan Le did an, an engineer by the name of cracked the EPOC's relatively weak encryption and posted an. This code sat in a proof-of-concept state for several years (during which unsuccessfully attempted to make it do something useful like connect to OpenViBE).
It was then taken up by and developed further, though as far as I know there is still not a way to connect the Emokit driver to OpenViBE or other analysis software. Emotiv Insight Emotiv Insight (5 channel dry-electrode headset)The newer (funded with a ) starts at $358.95 and has five dry electrodes at 10–20 locations AF3, AF4, T7, T8, and Pz.
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The insight has 14 bit ADC resolution, and transmits data over Bluetooth Low-energy 4.0 at 128 samples/second per channelEmotiv’s software runs on Windows, Mac, iOS, Android, and Linux.Further reading:.Versus: Dry-electrode neurofeedback headset for peak performance Versus dry-electrode neurofeedback headset with headphonesThe is a unique consumer EEG headset designed for athletic peak-performance neurofeedback training. It has integrated headphones for audio feedback.The versus costs $399.95 and has five dry electrodes at 10–20 locations CZ, C3, C4, FZ, and PZ, with one ear-clip reference electrode.
It transmits data over Bluetooth Low-energy 4.0.Versus was recently the topic of some. Melon: Neurofeedback headband Melon headbandThe is a slim EEG headset for focus neurofeedback. The Melon costs $149, has 4 dry electrodes, and transmits data over Bluetooth Low-energy 4.0.The Melon is currently out of stock, and their website states that they’re “back in the lab crafting new things.” iFocusBand: another neurofeedback headband iFocusBand headbandis a neoprene headband with three flexible woven electrodes and a 2-channel EEG amplifier. It’s targeted primarily at sports performance focus training, comes with a smart phone app, and costs $500.
Technical information is difficult to find on the company's website, but based on their very brief, it appears to record at 256 samples/second and transmit data via Bluetooth. Other DevicesHere are three interesting products that didn’t get fully funded, or have experienced unexpected delays and haven’t yet shipped to the public.pledged 1.9 million dollars to bring ’s EEG sleep headphones to the masses.
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Their goal was $100,000. Kokoon’s headset provides calming audio and and detects your sleep cycles. The Kokoon ranges from $219 to $349 for the developer edition.ran a for a pair of neurofeedback glasses that used the tint of the lenses as a neurofeedback modality for focus. The Narbis has 1–2 channels and uses dry electrodes at 660 samples/second with a 24bit ADC.
Data is sent over Bluetooth 4.0, and the Narbis is compatible with Windows, Mac, iOS, and Android operating systems. The Kickstarter campaign fell short of its goal — nerdy-looking neurofeedback glasses that blank out when you get distracted seem like a bit of a niche product — but their website indicates that they’re still working on the headset. Despite my skepticism of Narbis’ industrial design, I have to give them credit for being very straightforward about their, right down to schematics.was in Dec 2013, but they failed to ship to their backers on schedule. An update on November 12 th, 2015 said that mass production of the dream mask had begun.
The Aurora is available for pre-order on their website for $299.Postscript: tDCS & Other Things I’m Afraid OfThe devices I've covered so far are all designed to capture electricity coming out of your brain. Neurotech doesn't end there, though; a growing number of devices are available to put electricity into your brain. This is known as neurostimulation, and most of the devices use a version called Transcranial Direct-current Stimulation. Says Wikipedia:Transcranial direct current stimulation (tDCS) is a form of neurostimulation which uses constant, low current delivered to the brain area of interest via electrodes on the scalp. — WikipediaThe is skeptical, but although it claims that “Studies on healthy adults have failed to find evidence of cognitive improvements”, it also states that “there are no known risks of tDCS at this time” — and if that’s so, it shouldn’t hurt to test it out yourself with the proper safety precautions.I haven’t tried neurostimulation in general, or these devices in particular, myself; I can’t say much about them other than that they exist, and I’m keeping a watchful eye on them. The OpenBCI tDCS Shield OpenBCI tDCS shield prototypeFunded by a stretch goal on OpenBCI’s Kickstarter campaign for the Ganglion and Ultracortex, the for $49.99. If you’re into experimenting with tDCS and like the freedom (and occasional frusteration) of open-source, this seem like a good way to try it out.It stacks onto either the original OpenBCI or Ganglion board — it can’t run on its own.
The OpenBCI+tDCS combination opens up the interesting possibility for simultaneous neurostimulation and EEG recording. The tDCS sheild will also be compatible with the Ultracortex, by using adapters for the tDCS electrodes.Like the OpenBCI, OpenBCI Ganglion, and Ultracortex, the tDCS sheild is open-hardware, so you can modify it if you dare.
Its operating voltage is 12v, and its constant-current output is adjustable, manually or digitally, from 0–2mA. Focus: Electrical Brain Stimulators Focus Go Flow’s line of neurostimulation devices starts with the amazingly cheap, at $ 14.99 $149.99 — a tiny widget that snaps onto a 9 volt battery and provides transcranial direct current stimulation, which can be adjusted from 5 minutes at 0.5mA to 35 minutes at 2mA.
The current and time can’t be set independently.Their flagship product is the, which they bill as “The Worlds Most Advanced Electrical Brain Stimulator”. The Focus v2 supports a plethora of different types of neurostimulation: tDCS, or transcranial Direct-Current Stimulation; tACS, or transcranial Alternating-Current Stimulation; tPCS, or transcranial Pulsed-Current Stimulation; and tRNS, or transcranial Random Noise Stimulation. It even has a double-blind sham mode! The Focus v2 has apps for Mac, Linux, and Windows, and mobile, and sells for $299. Focus v2 in charging dockI’m much more likely to trust the claims of companies that have a good signal-to-noise ratio between legit science and marketing-speak. If they tell you what their product does and how it works, and their marketing is backed up by data, I appreciate it.The Focus scores fairly well on all of these counts. The hardware isn’t open-source, but their Android app is, and they’re at least upfront about the types of stimulation their devices provide, including power, voltage, and frequency.
You can find all that fun stuff over on their. Thync: tDCS + TENS Stimulation Thync (with electrodes)supports both tDCS and TENS. To learn more about TENS, I turned to Wikipedia:A typical battery-operated TENS unit is able to modulate pulse width, frequency and intensity. Generally TENS is applied at high frequency (50 Hz) with an intensity below motor contraction (sensory intensity) or low frequency (.