Frequently Asked Questions
The great thing about OpenBCI is that it’s totally open source. At this point in time, building on top of the OpenBCI Brainwave Visualizer or building unique applications does require some basic programming knowledge. With that said, our mission is to lower the barrier of entry so that even amateur developers can get up and running right away. With the post-Kickstarter release of the OpenBCI Board V3, we will be supplying thorough starter guides and suggested first project implementations with step-by-step instructions.
As more people adopt the OpenBCI technology, we will encourage our growing community of adopters to give back by sharing their personal research and development methods. We plan to expand the OpenBCI website to include a “Getting Started” section. In addition, we will be coordinating competitions to foster projects that continue to the lower the barrier of entry to interfacing the brain with the OpenBCI platform.Last updated:
The Electrode Starter Kit does not include the electrode cap seen in the video. In the video we are using Electro-Cap System I sold by Electro-Cap International, Inc. It can be found here: http://www.electro-cap.com/index.cfm/prices-additional-caps-and-supplies/systems/
A similar cap can be found in the following link, sold by Biopac Systems: http://www.biopac.com/electrode-cap-large
These caps are pretty pricy. That is why we are assembling The Electrode Starter Kit, which comes with passive gold electrodes and adhesive conductive electrode paste. This is a great starting place without having to spend a lot of money on the electrode cap. We will be buying the gold electrodes and paste in bulk and assembling cheap starter kits to distribute with the sets.Last updated:
Every reward that includes and OpenBCI board will also include a battery pack for local power supply.Last updated:
The OpenBCI board is based on the Texas Instruments ADS1299 chip, which has a sample rate ranging from 250 Hz to 16 Khz. We’ve tested and verified streaming 8 channels of raw, 24-bit EEG over USB serial into a computer at 512 Hz. We’ve tested and verified 16 channels of raw, 24-bit EEG into a computer over USB serial at 256 Hz. As we continue testing and verifying BTLE data rates we will update this FAQ.Last updated:
Our primary reason for moving away from the Arduino-shield form factor of OpenBCI board V2 is safety. Safety is our number 1 priority, and we want to ensure that we make it physically impossible to ground yourself to a wall while using the OpenBCI platform. To release the Arduino-shield form factor, it would require allocating lots of resources for engineering and testing to ensure safety.
With that said, the OpenBCI board will have exact capability of a standard Arduino and will be programmable through the Arduino IDE. The programming will happen over Bluetooth 4.0 LE instead of USB serial, however.Last updated:
In short, no. The OpenBCI board will come with a ribbon cable assembly that has the industry standard “touchproof” connectors as shown in the photo in our story. If you are interested in purchasing your own electrodes, there are a number of online distributers that sell different quality EEG electrodes. Not all electrodes will work with EEG systems. Because EEG systems have very low voltage levels (microvolts), you must use electrodes that have very low impedance. Today, most researchers are working with Silver Silver-Chorlide (Ag Ag/Cl) electrodes. Ag Ag/Cl is generally accepted as the best metal to conduct EEG signals.Last updated:
See above.Last updated:
One of the major design challenges of making EEG data meaningful is looking at how electrical activity in one region of the brain compares to electrical activity in another. The more nodes you have collecting EEG, the better the spatial resolution of your data. By having more electrodes you are able to isolate smaller regions of the brain. With fewer electrodes you are able to look at the brain as whole.
One popular application requiring higher electrode counts is detecting activity in the motor cortex of the brain for classifying the body’s movement. The motor cortex is a thin strip that stretches from ear to ear across the top of the head. When the body is relaxed and in an idle state the motor cortex produces a mu wave (around 13 Hz). This signal is harder to detect than the Alpha rhythms that are easily detectable in the occipital cortex at the back of the head; we demonstrate the ease of detecting alpha in our video and it can be seen in the OpenBCI Brainwave Visualizer in our story.
We foresee a lot of OpenBCI adopters trying to detect and classify the mu rhythms of the motor cortex to build systems that enable virtual control of objects. A system like this will be much more powerful with many electrodes concentrated over the motor cortex, detecting intended movement of one limb versus another. For more information, check out Chip’s comprehensive post on detecting mu rhythms with OpenBCI: http://eeghacker.blogspot.com/search/label/Mu%20Waves
In summary, more electrodes equate to more granular recording of one region of the brain versus another and allows for more complex classification of electrical brain patters.Last updated:
Our 'Researcher & Developer At Large', Chip, has done some EOG measurements using the OpenBCI V2 board. His experiments can be found here
The OpenEEG Project is an amazing open-source EEG initiative that was started in the early 2000s. The big difference between OpenBCI and OpenEEG is that we are focusing a lot of our efforts on driving down the barrier of entry to brain-computer interfacing, as opposed to just providing an out-of-laboratory option to research-grade EEG. If our Kickstarter campaign is funded, we will be creating numerous how-to guides for novice programmers while still providing a system that is enticing to experienced engineers and programmers. In addition, community outreach is one of our main goals as well. We will be coordinating hackathons geared towards brain-interfacing enthusiasts of all ages and backgrounds. Design, instruction, and approachability are a big part of our vision.
On a more technical note, OpenBCI has a 24-bit ADC instead of OpenEEG being 10-bit. This is a HUGE difference in dynamic range, enabling OpenBCI to do really small signals (EEG), bigger signals (ECG on the wrists), and huge signals (ECG on the chest, EOG, and EMG) all on the same device without clipping or saturation. With OpenEEG, if you do ECG on the wrists, your signals are just barely small enough to fit within OpenEEG's limits. For ECG on the chest, the signals are too big for OpenEEG and your ECG signal shows up on the computer as being clipped. In sum: OpenEEG has a limited dynamic range (10-bits) that is tailored only for EEG. OpenBCI has a wide dynamic range (24-bits) that allows it to support all of these biopotential sensing applications.Last updated:
We will be hosting a number a few mini-lectures and hackathons over the course of the Kickstarter campaign. On December 16th we will be doing a lecture and live demonstration of the OpenBCI technology at CultureHub in NYC. See event details here: http://www.meetup.com/volumetric/events/153921762/
As more meetups are organized we will be sure to keep all of our backers and the broader OpenBCI community informed.Last updated:
What's the difference between the 8-bit core Arduino Compatible and 32-bit core ChipKIT Compatible micro-controllers?
If you're wondering which core you should go with, here's a little info to start you off: The 8-bit core runs at 16MHz, and the 32-bit core runs at 50MHz. ATmega328 comes with 32KB of flash program memory space, and the PIC32MX250F128 comes with 128KB of flash program memory.
Specifications on the ATmega328 can be found here
Specifications on the PIC32MX250F128 can be found here
We encourage all backers that are using or plan to use the Daisy-Chain Kit to select the 32-bit PIC32 core. It is a more powerful internal hardware design, capable of faster data rates at higher channel counts. The 8-bit option will be preprogrammed with the Arduino bootloader, making it instantly programmable with all Arduino code. The chipKIT development environment (used with the PIC32 core) is based on the Arduino IDE, but modified to support PIC32. It is compatible with many existing Arduino code examples, reference materials and other resources. Please send us questions that you have through the Kickstarter message portal if you have any. Be sure to do your own research as well, to be certain you maximize your OpenBCI reward!Last updated:
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