NextMind Sensor EEG

A beginner’s guide to EEG & the NextMind Sensor

The electrodes in our Sensor are the basis for our Brain-Computer Interface. Find out what they are and how they work.

The first step to interpreting brain data into digital commands is sensing brain activity. Learn everything you need to know about EEG measurement in this article.

Brain basics

Your brain consists of billions of neurons that emit electrical signals as they pass information between themselves. When enough of them are active, they create an electrical field that can pass through tissue, bone, and skull. By reading these signals, we can start to understand what’s happening in the brain. 

This is an anatomically-realistic 3D brain visualization based on real-time EEG signals
Credit: UCSF Neuroscape

The most common ways of measuring brain activity are functional Magnetic Resonance Imaging (fMRI), magnetoencephalography (MEG) and electroencephalography (EEG).

These are all non-invasive methods, which mean that signals are collected from outside the brain. Other Brain-Computer Interfaces (BCI) are invasive and require surgery to implant chips or other materials inside the head.

Why choose EEG?

Using EEG in our Sensor was an obvious choice. EEG has been used extensively since the 1930s [1], so we know this is a safe and trusted technology.

It is a passive tool that can pick up changes in electrical signals and does not send out any signals. You can think of it as a microphone for the brain [2]. The fact that it’s non-invasive also makes it easier to use for more people. 

It’s important to not only pick up data instantaneously, but also ensure it’s high quality [3]. This can be difficult since the electrical charges your brain creates are tiny and constantly fluctuating. But EEG can detect all of this within the millisecond, even through the skull. 

Then to ensure high quality data, we spent years designing our Sensor hardware. Innovative materials and sensitive electrodes allow us to more clearly read the signals we’re looking for. 

An upgraded EEG experience 

Most EEG devices you’ve seen have probably been in a medical or scientific context. To capture as much data as possible, they usually cover the entire head and set-up can take up to 20 minutes. Gel is needed to help electrodes pick up as many electrical signals as possible.  

This is a suitable method for gathering lots of data in a research or medical setting, but not for everyday use

NextMind EEG compared to medical EEG cap
The NextMind Sensor uses EEG technology often found in medical devices, but completely redesigned for everyday use.

Using the knowledge from our academic background, we redesigned and improved upon existing EEG hardware.

Since we focus on interpreting visual cues, we only need to read data from the visual cortex. Targeting this zone on the back of the head allowed us to make our device quite small. Our Sensor has only 9 electrodes compared to the 30+ needed for medical EEG headsets. 

Since our goal was to create a device that’s discreet and easy to use, we replaced cables with a Bluetooth transfer. And instead of gel, we designed dry electrodes. When in direct contact with the scalp, a special polymer material conducts the tiny electrical signals from your brain.

The result is a Sensor that you can put on in only a few seconds and wear for hours. 

Thanks to feedback from our Dev Kit users, we are continuing to improve the design of our Sensor. This work is leading us to solutions that will help drive mass adoption of BCIs. 

Have questions about our technology? Drop a comment below and we’ll do our best to cover it in future articles. 

References 

[1] Berger, H. (1929).Über das elektroenkephalogramm des menschen. Archiv für psychiatrie und nervenkrankheiten87(1), 527-570. https://doi.org/10.1007/BF01797193

[2] Schomer, D. L., & Da Silva, F. L. (2012). Niedermeyer’s electroencephalography: basic principles, clinical applications, and related fields. Lippincott Williams & Wilkins. 

[3] Wolpaw, J., & Wolpaw, E. W. (Eds.). (2012). Brain-computer interfaces: principles and practice. OUP USA. 

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