4 ms·
You can detect strong signals with current consumer technology. One easy pattern is the SSVEP[1], which shows up as a spike in the brain signal's FFT at the fre
by leggomylibro 10y ago
You can detect strong signals with current consumer technology. One easy pattern is the SSVEP[1], which shows up as a spike in the brain signal's FFT at the frequency of a flashing light that the subject is looking at. Interestingly, it also seems to work with binaural audio.
It might be hard to tell peoples' signals apart with the confidence of a strong password, but individuals do respond pretty differently in terms of how long it takes to appear, how quickly it grows, how much of a spike is observed, small offsets, etc.
[1] https://en.wikipedia.org/wiki/Steady_state_visually_evoked_potential https://en.wikipedia.org/wiki/Steady_state_visually_evoked_p...
- lettergram 10y agoYeah, SSVEP has it's uses[1], but I don't think it would work well enough to identify various users with any sort of confidence. It would likely be easier to do with showing an image (or series of such) that would present people with a very different emotional responses. This could be loved ones, childhood homes, etc. If you are curious in this stuff, I am pretty familiar with this stuff, and my startup[2] uses consumer EEG's regularly. Our single largest concern is actually signal correction due to movement / other environment factors[3]. [1] http://synaptitude.me/blog/a-quick-intro-to-ssvep-steady-state-visually-evoked-potential/ http://synaptitude.me/blog/a-quick-intro-to-ssvep-steady-sta... [2]http://synaptitude.me/ http://synaptitude.me/ [3] http://synaptitude.me/blog/using-computer-vision-to-improve-eeg-signals/ http://synaptitude.me/blog/using-computer-vision-to-improve-...