Commit 3e322c6c authored by Adrien Dorsaz's avatar Adrien Dorsaz

Add a plot for final presentation and R script to make boxplots

parent f8c53f3c
pocketbrain=read.table(args[1], col.names=c("arousal", "valence", "emotion", "time"))
arousalCalm <- read.table(args[2], col.names= c("calm"))
arousalExited <- read.table(args[3], col.names= c("exited"))
boxplot(calm, arousal, exited, main="Arousal boxplots", names=c("Calm", "Movie arousal", "Exited"), outline=FALSE, horizontal=TRUE)
arousalPs = paste(args[1],".arousal_",tail(time, n=1), ".pdf", sep='')
valencePositive <- read.table(args[4], col.names= c("positive"))
valenceNegative <- read.table(args[5], col.names= c("negative"))
boxplot(positive, valence, negative, main="Valence boxplots", names=c("Positive","Movie valence", "Negative"), outline=FALSE, horizontal=TRUE)
valencePs = paste(args[1],".valence_",tail(time, n=1), ".pdf", sep='')
Video with Game of Thrones generic and boxplots
Game of Emotions
# The one who control his emotions, can...
* keep calm in any condition
* improve expression of what you want
* improve expression of how you feel
* improve how other feel you
# So, he can be on the FER throne
Indeed, he will be "master of his emotions"
So he can take the best decision in every situation
And he'll never be manipulated by others
# But the question his learn to control emotions ?
# With help of emotionless computers !
# Computer to control emotions ??
## Computer can _measure_ your emotions :
* it determines how you feel with 2 values :
* arousal : are you _calm_ or _exited_ ?
* valence : feel you _positiveness_ or _negativeness_ ?
## But you have to train it :
* So it knows what is your _brain activity_ for each emotion you have
* And it can apply _statistics_ to know which are your current emotion
# Computer isn't really _PORTABLE_ ...
Use your Android phone !
Smartphone are _real computers_ now !
# Wait, you've said "measure brain activity" ? We'll have to go in _hospital_ ?
No, you'll be able to do it every where with emotive headset!
# Wow, a so small headset is enough accurate ?
If you train enough your computer, you'll have some good result
# Enough words, have someone done it ?
All on github :
# Show me !
* capture application with Game of Thrones and explication
* capture of PocketBrain and UI explanations : TRAIN
* capture of PocketBrain and UI explanations : TRY
## Which are key piece ?
# Emocap headset
* closed software (so encrypted communication)
# Emokit open-source project
* decrypt data from headset
# SmartphoneBrainScanner2 project
* provide a lot of tools to
* get data from headset
* apply some filters on them
* make application for Android
# AOSP (open-source Android code)
* To use your phone as you want
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