Hello OpenBCI community!

This month we want to show our appreciation for professors and teachers around the world who are doing their best to provide academic instruction in these times. Scroll down to get the discount code for free international and domestic shipping on select orders.

Other announcements include an incredible research highlight on biometric authentication, as well as a community-contributed motor imagery tutorial. We hope you enjoy these updates, or better yet, try them yourself!

This month we also have an interview with Guillermo Bernal, one of the key engineers at OpenBCI, and a PhD candidate at the MIT Media Lab. We sat down with Guillermo to discuss his work exploring the intersection of human-computer interfaces and mixed reality (XR). Keep an eye out for exclusive news about the product of our collaboration with Guillermo, in next month's newsletter!

2. Research Highlight

This month's OpenBCI Research Highlight goes to "Blink to Get In: Biometric Authentication for Mobile Devices using EEG Signals," published by Ekansh Gupta, Mohit Agarwal, and R. Sivakumar, out of the Georgia Institute of Technology in Atlanta.
From the paper,
"Biometric authentication has fast evolved to be the default authentication mechanism on smartphones and other mobile devices. With users facing an authentication challenge dozens of times in a single day, there is a distinct need for an approach that is both lightweight in terms of user burden and strong in terms of secureness. In this paper, we consider a more accessible physiological data for a user – the user’s electroencephalogram (EEG) data for a specific action – blinking. With EEG growing to be a bonafide input modality in several commercial applications such as healthcare, gaming, and wellness, and the consequent wider availability of EEG headsets off-the-shelf, access to a user’s EEG data is easier than it has ever been." Methods:

The researchers used the OpenBCI Cyton 8-channel Board and an electrode cap to sample EEG signal from 20 subjects. They obtained a dataset of EEG signals through controlled experiments where the users are prompted to blink, and the corresponding EEG signal are collected and processed (shown below). Read their paper to learn more about the methodology!

Takeaways:

The authors established proof-of-concept for blinking as an input for reliable biometric authentication, using the widely accepted idea that EEG signals associated with blinking are strongly identifiable, and more importantly, repeatable. In the paper, a set of systematic strategies to improve the data features was presented to show that it is indeed possible to devise an effective authentication solution. The dataset (partially pictured above), was used to evaluate the algorithm. The authentication solution, using the subjects' EEG signals captured when blinking, achieved an accuracy of 92%.

Learn how OpenBCI products have been used to conduct neuroscience research since 2015 with the OpenBCI Research Collection, a resource we update frequently. If you'd like to submit your paper for consideration, don't hesitate to reply to this email or reach out to contact@openbci.com.

3. Meet the OpenBCI Team: Guillermo Bernal

One of the advantages of being an open source company is the way it enables unique opportunities for collaboration which would otherwise not be possible. Over the past 2 years, OpenBCI has been collaborating with MIT Media Lab PhD candidate Guillermo Bernal on exploring the intersection of human-computer interfaces and mixed reality (XR). Head to the community page to learn more about Guillermo, his work, and upcoming news on his collaboration with OpenBCI.

From the article:

"My goal is to help create technology that can adapt to the user’s state, and intervene or disappear as needed. I think the ideal cognitive support tool is one that gets you to a point where you no longer need it, not something you become highly dependent on. I want the metrics and devices that emerge from my studies to create new tools that aid the subjective process of creativity."

4. New Tutorial: Motor Imagery

For his step-by-step tutorial using OpenBCI to capture and use motor imagery data, this month's community member of the month award goes to Rakesh Jakati!

Method:
Using the OpenBCI All-in-One EEG Electrode Cap Kit, Rakesh set up (and documented) a brain-computer interface system that allows a user to directionally control a system by imagining different movements of their limbs. The tutorial goes into detail about setting up the hardware and software, as well as recording and processing the data. Amazing work! We love to see this kind of community-contributed content!

Calibrating the system

Following this tutorial, you will be able to design your own Motor Imagery Classification demonstration with your own data and control cars, drones, and other devices. Bring your imagination to life with open-source neuro-hardware—we'd love to see what you create!

From everyone at OpenBCI, we want to say thank you. The inertia for the emerging technologies we work with is snowballing, and we're excited to keep you in the loop! Your support is making the open-source Neuro-revolution possible. We look forward to getting the latest OpenBCI technology into your hands. If you have any questions, comments, or concerns, don’t hesitate to reach out: contact@openbci.com.

From the OpenBCI team, we heart you!

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What's New at OpenBCI

1. Free worldwide shipping for orders over $999

2. Research Highlight

3. Meet the OpenBCI Team: Guillermo Bernal

4. New Tutorial: Motor Imagery

Thank You!