Tag Archives: EEG

QS Los Angeles Meetup Recap

This guest post comes to us from QS Los Angeles member, Mark Krynsky.

I went to the Los Angeles Quantified Self Meetup meeting on March 7th and had a fantastic time meeting like-minded people that are all willing to experiment and share their experiences. The meetup was held at the artisanal engineering studios of the Two Bit Circus located in the eclectic Brewery Art Colony. This made for a really great venue.

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Photo from QS LA taken by Eric Blue

The first speaker was Brent Bushnell who is the Circus ring leader. He walked us through a project his team worked on for the Extreme Makeover Home Edition where they built a relaxation chair for a veteran that suffered from PTSD. They used sensors to track his biometrics to help identify when he may be susceptible to trauma. When certain thresholds were met based on his heart rate the soldier would sit in the chair which would then play soothing sounds and had an aroma therapy device.

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Jakob Eg Larsen and Yoni Donner on Cognitive Measurements

Another breakout session preview for the upcoming QS conference: feel free to connect with the leaders in the comments!

Here are Jakob Eg Larsen and Yoni Donner, who have both created tools for quantifying mental performance, describing their session “Cognitive Measurements:”

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Measuring cognitive functions is difficult but provides a much richer understanding of ourselves compared to single-dimension measurements (such as steps taken, heart-rate and weight) that have been the primary focus of the QS community.

One approach to measuring cognitive functions is behavioral: inferring cognitive state from our actions and our ability to respond to stimuli. This lies at the heart of traditional psychometrics, the field of psychology concerned with such measurements. Unfortunately, traditional psychometrics mostly focused on measuring differences between individuals, treating a person as a single data point and comparing them to the general population. In QS, we care about within-person variation: how do our cognitive functions vary at different times and how does this variance relate to our actions? This kind of knowledge can lead us to choose actions that lead to desired cognitive outcomes.

Quantified Mind is a tool designed specifically for measuring within-person variation in cognitive abilities and learning which actions we can take to influence our cognitive functions. In other words, what makes you smarter? It uses short and engaging cognitive tests that are based on many years of academic research but modified to be short, repeatable and adaptive. Quantified Mind can be used by any individual to learn about their own brains, and also invites users to participate in structured experiments that examine common factors such as diet, exercise and sleep.

In the session we will also briefly discuss the ‘Smartphone brain scanner’ — a low-cost portable cognitive measuring device that can be used to continuously monitor and record the electrical activity (EEG) along the scalp in order to determine different states of brain activity in everyday natural settings. The system uses an off-the- shelf low-cost wireless Emotiv EPOC neuroheadset with 14 electrodes, which is connected wirelessly to a smartphone. The smartphone receives the EEG data with a sampling rate of 128 Hz and software on the smartphone then performs a complex real-time analysis in order to do brain state decoding.

Please join us to discuss these topics, and bring your questions and engaged minds!

 

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Martin Sona on EEG for Self-Experimentation

With the QS conference around the corner, we’re asking our breakout session leaders to preview their topics here on the blog. There will be many overlapping sessions to choose from, so here’s your chance to learn more about what you want to see, and connect with the leaders in the comments.

Here is Martin Sona, organizer of QS Aachen/Maastricht, on his session “EEG for Self-Experimentation:”

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The subject of this breakout session will be experimentation with electrophysiological methods, such as electroencephalography (EEG).

First, a short introduction will shed some light (not a lot though…) on the puzzling phenomenon of  ’brainwaves’. Í’ll also tell something about how an EEG works, what the pitfalls of this method can be.

Consequently, you’ll get a short overview of the EEG ‘market’ accessible to enthusiasts and we’ll visualize some data very quickly. There will be some room for questions, but if you have a particular question in mind, feel free to email me and I’ll try to answer it during the session.

 

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Jakob Larsen: My Experience with a Smartphone Brainscanner

 Jakob Larsen and his team at the Mobile Informatics Lab at the Technical University of Denmark have developed a way to build a real-time 3-D model of your brain using a smartphone and the Emotiv EPOC game controller headset. In the Ignite talk below, Jakob describes how the fourteen sensors in this mobile EEG device rival a traditional lab EEG setup, and where he sees this inspiring project going. (Filmed at the QS Europe conference in Amsterdam.)

My experience with a smartphone brainscanner by Jakob Eg Larsen from Quantified Self Amsterdam on Vimeo.

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Personal Informatics In Practice: A Cross-Platform Smartphone Brain Scanner

This is a guest post by Jakob Eg Larsen, an Associate Professor at the Technical University of Denmark (DTU) at the Cognitive Systems Section where he heads the mobile informatics lab (milab). His research interests include human-computer interaction, personal informatics, and augmented cognition.

Better understanding of the intricate relations between our brains and behaviors is key to future improvements in well-being and productivity. Conventional tools for measuring these relations such as functional magnetic resonance imaging (fMRI) or positron emission tomography (PET) typically rely on complex, heavy hardware that offer limited comfort and mobility for the user. This means that measuring brain activity has been confined to expensive laboratories and that it has been a challenge to perform longer term continuous monitoring of brain signals in real life conditions.

Electroencephalography (EEG) is a method for recording the electrical activity along the scalp. EEG measurements can determine different states of brain activity, for instance is this signal used by the popular Zeo Sleep Manager to determine when the user is in different sleep stages, using just a few electrodes. More electrodes enable a richer picture of the brain state and in laboratory settings typically 64, 128, or 256 electrodes are used. However, these systems are time consuming and cumbersome to install and their wiring limits user mobility and behaviors.

With our ‘Smartphone Brain Scanner’ system we aim to enabled continuos monitoring and recording of brain signals (EEG) in everyday natural settings. For that purpose we use an off-the- shelf low-cost wireless Emotiv EPOC neuroheadset with 14 electrodes, which we have connected wirelessly to a smartphone. The smartphone receives the EEG data with a sampling rate of 128 Hz and our software on the smartphone then perform a complex real-time analysis in order to do brain state decoding. That is, estimate the sources from which the brain activations occurred and then show the result in a 3D model of the brain on the smartphone display. This allows the user to observe his/her brain activations in 3D in real time. The video below provides a demonstration.

The smartphone brain scanner enable complete user mobility and continuous logging of brain activities either for real-time neuro feedback purposes or for later analysis. The user can interact with the 3D brain model on the device using touch gestures and the system allow up to 7.5 hours continuos recording.

From a personal informatics perspective the ability to obtain continuous bio-feedback is interesting as it has been shown that such bio-feedback may lead to improvements in behavior, reaction times, emotional responses, and musical performance. Within the clinical domain it has been shown to have a positive effect on attention deficit, hyperactivity disorder, and epilepsy. For such applications a low-cost and easy-to-use brain monitoring system enabling complete mobility could be beneficial. Furthermore, the ability to monitor and record brain signals over longer durations in natural settings might allow the user to gain new insights, and the low-cost setup even allow studying EEG signals in group settings.

More information about the smartphone brain scanner is available here: http://milab.imm.dtu.dk/eeg

With a Nokia N900 and the Emotiv EPOC headset you can try the system for yourself by downloading the brain scanner software from the Maemo repository. We also have a version for Android-based smartphones and tablets, however the software is not released yet.

This article is a summary of a position paper by Jakob Eg Larsen, Arkadiusz Stopczynski, Carsten Stahlhut, Michael Kai Petersen, and Lars Kai Hansen that will be discussed at the Personal Informatics in Practice workshop at CHI 2012 in Austin, TX on May 6, 2012. The workshop will be a gathering of researchers, designers, and practitioners exploring how to better support personal informatics in people’s everyday lives.

 

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iBrain tracks sleep – to what end?

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QS Show&Tell regular David Duncan, author of the upcoming Experimental Man, blogged last week about his experience with the iBrain, a single electrode brain wave monitor under development by Philip Low, a neuroscientist and founder of Neurovigil, a startup that is commercializing his single electrode device for clinical and home use.  The picture at left is a standard EEG set-up, shown here on a hospitalized child with Aicardi syndrome. Other EEG set-ups involve a cap or helmet. There are many  uses for a simpler and more informative EEG. (The value, obviously, is not in sticking a single electrode to the scalp, but in understanding the data – this is the area of Low’s reseach and Neurovigil’s patents.)

Duncan does not learn very much from his experience with the iBrain – his sleep patters are typical. But self-quantifiers will immediately recognize the interest such a device holds, not just for comparing an individual’s sleep to a “typical” sleep pattern based on data from many users, but for correlating one’s own sleep with other data generated by other self-monitoring systems and devices. Sleep is known to correlate with learning, mood, respiratory and cardiac health, and many other measurable dimensions of life. A simple, single electrode system for measuring EEG at home would be add a tremendous data source; while, of course, deeply taxing our analytical skills and hypothesis-generating creativity.

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