After five years of consistently blogging, and consistently failing to do something about it, the BCI-building has begun. The academician in me needed an outlet and I’ve been craving for something hardcore technical for a while now. So begins the first formal attempt at building a cheap home-made BCI. I’m going to label all entries so that it will be easy to follow progress on this.
Unlike my regular posts which are composed with at least some thought, this series of entries will be more like a journal. I’ll post entries with what I do, what methods I follow, everything I try. With any luck, there should be enough detail that anyone could replicate what I am doing with full fidelity. The attempt at any original research is not even a long-term goal. The goal here is to, and I say this as directly as possible, with no misconceptions whatsoever, and no subtext, “to have fun.”
If you have any interesting theories, experiments, I would love to hear your thoughts. If you’d like to participate, you’re welcome to join. Most followups will be brain-dumps of my thoughts – unedited, raw, and naive. A side-effect of this blog is to also demonstrate any points of failure, or stuff that doesn’t work. At this point, I have nothing working. I don’t want to claim that I knew everything, in case I succeed. I won’t use the excuse that I never wanted to succeed in case I fail. I want to make this work, and even if it doesn’t, it won’t change the fact that I still wanted it to work. If I make a mistake it’s going to be published, since I will try and publish what I intend to do before I do it as a validation.
At the moment, I picked the PocketEEG from PocketNeurobics (apparently an Australian company) to get started. I’ve been out of this world for a while (four years), and it takes a long time to catch up on the IEEE Journal of Biomedical Engineering where most BCI work is (used to be?) published. The WaveRider system is a clinical device but it costs too much for me at the moment, but if this device fails, I’ll save up for the WaveRider and go with it. It’s a two-channel device.
I haven’t got the electrodes yet, so haven’t taken any readings, but plenty of work has to happen before the electrodes become relevant. The recommended software to be used with it is BioExplorer which I think costs too much. I instead tried to connect the open-source BioEra software. The UI takes me back to the good old colleges days before the polished world of iPhones and iPads. It has a way to define the processing pipeline but I rather hate doing it graphically. The dongle does provide a fake serial port on your PC that you can read from, but I didn’t want to go through that much trouble. I intend to use BioEra to capture the signal and send it across a local TCP channel into a server I’ll write that does what I want it to. BioEra seems to support plugins, but I love the flexibility of having my own executable as opposed to being “hosted in” another exe.
This pipeline investigation should take until the weekend, and hopefully I’ll have it coded over the weekend. If I’m lucky, and the electrodes to arrive, I’ll be sure to post some recordings of motor activity of right and left hands, captured from the C3 and C4 points at the beta band.
The reason I don’t want to use the provided FFT block is because I much rather enjoy playing with parameters initially. Do I want it sliding window at every point or will I perform it on intervals? If I intend to do something like auto-regression, I’d much rather use my own buffers and optimize the pipeline to operate on. I’ll post what happens.
Sweet! Good to know you’re finally starting
! Best of luck. Hope it does work. This is awesome!
Comment by Dhruv Sood — April 1, 2011 @ 10:27 am
I am a bit intrigued by how you test if a particular signal processing approach you use is working. Do you first run it against something like the EEG data here : http://sccn.ucsd.edu/~arno/fam2data/publicly_available_EEG_data.html
or do you have your own dataset ?
Comment by Shriphani Palakodety — April 2, 2011 @ 12:31 pm
I’m glad someone asked me the definition of “success” here.
The success criteria is replicating the 1992 Wolpaw, McFarland, et. al. experiment. Mouse cursor control over one degree of freedom. I still haven’t defined what “success” within that is, but success there is a continuous function as accuracy increases, and will depend largely on test subjects being able to learn too.
About your question on datasets, yes, for years, I’ve been working on the BCI Competition Datasets, though I never knew about the link you just posted. That certainly calls for some attention, but I don’t have the time I used to get for pure academic activity, so instead of just taking a break and doing nothing, I decided to try and build one for fun.
At the moment the very immediate experiment in my list is to find a correlation between motor activity and the signal components.
Comment by archisgore — April 12, 2011 @ 8:40 am