The Turing Normalizing Machine
To create a new classifier such as “surprise” we would need to get a baseline of raw EEG data. We will then introduce a the subject to a surprising stimulus and measure the difference in raw EEG data. We would need to repeat the process several times and have an average of the surprise stimulus data to be confident in the results. The problem here would be desensitisation to the stimulus. Over time the subject will be aware of the inducement and may fail to provide the appropriate surprise data. To counter this issue of desensitisation we would use multiple subjects. In addition to solving the desensitisation issue, we generate a more universal notion of the emotional state / classifier we are hoping to achieve. By analysing the patterns emerging from multiple surprise data response from different people, we can start to create a module for understanding a normalized physiological response based on a particular stimulus.
Brainstorm of ideas:
– baseline of surprise
– use a sweat sensor and the thinkgear
– raw eeg?
– surprise by playing a video
– measure heart rate
– emotional state that can be repeatedly tested
– emotions to consider: anger, fear, nervous, agitation(annoyance), sad, apathy, empathy, disgust
– have ppl look at optical illusions as stimulus?
– trigger: disgust, primal instinct, visceral, elicit instinct, fear
– map body’s physical chemical reaction with brainwave data
– use a person without stimulus as control
– test more ppl with stimulus
– possibly use brainwaves of other beings besides humans
– And It gives a universal response
– Stimulus, sound and video
– creating a new classifier, problem of being desensitized
– take difference btwn all the testers and come up with an average