Friday, September 18, 2015

Electromyograms for Researching the Brain?

I've had my eye on Electromyograms and Electroencephalogram technology since the VR bug first caught me. As of late, my inclinations towards using electromyograms have wained considerably from the place they were in back in 2013 and 2014, leaning more towards a more simplified system, but I've found another potential use for them in recent days. While it's possible this data is already available but I just haven't found it, I'm heavily interested in the formatting for the data that the human brain and nervous system use to transmit signals. Not in a, neuron pulse and axon pathways sense, but rather a more abstract, idea driven sense. Is the transmission something that occurs based upon the initial point of production? Where do they end up? Does the frequency of the signal matter? Is there a particular pattern that can be discerned out of the transmissions? This is key information towards developing a viable neural control system, regardless of the technology you're using for the purpose.

Electromyograms can detect the electrical activity of muscles, so I'm curious if we could compare the data between an electromyogram and electroencephalogram to determine if there are any correlations or clear causations that can be drawn. Perhaps our current sensors aren't sensative enough for the purpose, but it couldn't hurt to try I'd say. If I had to establish a methodology, I'd say the easiest method would be to go over individual voluntary muscle groups  using many sensors on each one involved in a set repetitive task. By having the task be repetitive, we can help to neutralize any unneeded data. Compiling more and more data in variations of the experiments such as using the same muscle group but in different tasks or having different muscle groups engage in a mechanically similar task, we could possibly discern if there's any particular set of models for the output of our movements. Would they be based on a particular operation like processing the location of a spatial location using proprioception and kinesthesia? Perhaps it's a simpler local rotation system or something more intricate using an archived library of possible position states. The rabbit hole here goes deep, but the value of the information could be useful well into the future in an innumerable amount of applications.

This is the sort of experiment that a lab and research team would be perfect for, so it's unlikely I'll be able to match up to the output such an environment could procure. It'd be great if I could join such a group one day, but if I can't, I think I'll give it a try in 2017. 2015 is wrapping up soon and I have plans for 2016. 2017 however should bring opportunities abound for this purpose, though I'm genuinely hopeful that teams will have been well into such experiments by such a point. The idea that we wouldn't be trying such a method if isn't invalidated by some kind of technological limitation would be infuriating.


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