For those that suffer them, seizures are a dangerous thing. Outside the neurological effects, there is always the possibility of injury from the surrounding environment as well – consider the dangers of having a seizure near a busy road, or even simply a glass table. Some detection methods exist for seizure sufferers, but they are primarily based on detecting the jerking motion of the patient. [akhil2001us] thinks it’s possible to do better – by measuring brainwaves to detect the onset of seizures.
The build is centered around the Neurosky Mindwave headset. This is an off-the-shelf product designed specifically for capturing EEG data. It outputs raw brainwave data which is key for doing proper analysis. The project then uses an Arduino Mega to tie everything together, along with some Sparkfun Bluetooth modules to talk to a cell phone to send an SMS for help in the event of a seizure.
The real difficulty in a project like this comes from developing an algorithm that can reliably detect seizures, as well as a unit robust enough to work in the real world. It’s no use if your headset is detecting a seizure in progress, but the help message is never sent because a wire fell out of your breadboard. It’s considerations like this, combined with the threat of litigation, behind why medical devices are so rigorously engineered and certified. For a proof of concept, however, such concerns are not as important.
We’ve seen Mindwave builds before – brainwave research is an exciting field!
For [Ern]’s MEng group project, his group had to develop a robotics platform capable of achieving some end goal. Because innovation is a large part of the grade, [Ern] convinced his team members to work with a brain controlled interface and build a mind controlled robotics platform.
For wont of having an easy build, [Ern] and his team chose a Lynxmotion Tri-Track robot capable of moving around the classroom while receiving commands from a computer. The mind-control portion of the build comes from a NeuroSky MindWave Mobile, a cheap and fairly open EEG system that reads alpha, beta, and delta waves generated by a user’s brain and sends that data over to a computer for processing.
After a bit of testing that included an Arduino to move the robot forward if the MindWave’s ‘attention’ value was over 60%, [Ern] and his team looked for a way to implement multi-directional control.
In order to get the robot moving left, right, and backwards in addition to moving forwards, the team looked at the included ‘blink detection’ abilities of the MindWave to cycle through a few commands. This technique turned out to be far too sensitive – the blink detection of the MindWave is simply too good. To get around that problem, the team used the signal strength of the received EEG signals. The theory being when a user blinks their eyes, the EEG contacts will move slightly, degrading the signal received by the hardware.
The team finally got a reasonable mind-controlled robot up and working, as demonstrated in the video after the break. Check out how each blink allows [Ern] and his colleagues to cycle through driving modes. Pretty neat for controlling something with your mind.
Continue reading “Controlling a robot with your mind”
Because switching apps to change a song is such a taxing ordeal, [Oscar Celma] and [Ching-Wei Chen] decided to use their collective brainpower to change Last.FM playlists with their minds. They call their project Buddhafy, and it works by taking off-the-shelf EEG hardware and tying it into music streaming APIs.
For the build, the guys used a NeuroSky MindWave to read alpha waves inside [Oscar]’s head. The data from the MindWave was passed into a Python script that sends requests to the Last.FM and Spotify APIs. High alpha waves in brain wave patterns correspond with concentration or a deep meditative state. If [Oscar] concentrates very hard, he’ll be rewarded with calm and relaxing tunes. If [Oscar] loses focus, the music changes to the best song ever written.
The guys put up the slides from the presentation they gave at MusicHackDay in San Fransisco this last week. There’s also a video of their build in action; you can check that out after the break.
Continue reading “Control a playlist with your mind”
[Chris] thinks that using your brain to control your trigger finger is a passé way of operating a toy firearm. Instead, he’s using his mind to fire foam bullets at whatever he thinks needs to pretend-die. To read his will, he’s chosen the Neurosky MindWave, a device that we just looked at for servo control. That hack shows how to patch into the USB dongle that comes with the device, but [Chris] opted to use a BlueSMiRF module from Sparkfun to connect the headset to an Arduino via Bluetooth.
The rest of the hack involves modifying the gun for automatic firing. It’s a Nerf Stampede, which takes six D-cells to power the electrical firing system. [Chris] didn’t want to carry that weight around in the body of the weapon itself so he installed a port for external power and added a firing mechanism at the same time. It uses relays to complete the circuit normally operated by the trigger. Now logic-level signals have no problem dispensing justice from the brightly-colored device.
Here’s a setup to control a servo motor with your mind. [Danny Bertner] made this project happen by interfacing a MindWave headset with an Arduino. You might wonder what’s the big deal about that since we’ve covered quite a few mind control hacks that work this way? So far, the majority of those hacks used the Mindflex toy (to be fair there were several using the Force Trainer as well), which depends on a chip made by the company that is responsible for the MindWave. Both the Mindflex and the Force Trainer were reverse engineered to access the stream of data coming in from the EEG sensors. But NeuroSky is embracing the urge to mess with their products by offering developer tools.
[Danny] took advantage of these resources, using the comany’s own guide to interfacing with an Arduino (PDF). The quick clip after the break shows his finished project, grabbing data from the USB dongle that comes with the headset, converting it to the necessary levels for the Arduino, then processing the signals for display on and LED bar graph.
We can’t help but chuckle about the warranty-voiding disclaimer at the top of the PDF guide.
Continue reading “MindWave is developer (read: hacker) friendly mind control”