Paper reading #35: Addressing the Problems of Data-Centric Physiology-Affect Relations Modeling

Reference Information
Title: Addressing the Problems of Data-Centric Physiology-Affect Relations Modeling
Authors: Roberto Legaspi, Ken-ichi Fukui, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao, Merlin Suarez.
Venue: IUI’10, February 7–10, 2010, Hong Kong, China.

Summary

Using a data-centric approach, the researchers of this paper attempted to come up with a way to use machine learning in order to define so called "affective states". Using an EEG helmet, the researchers attempted to classify, and define the different emotions that the wearer was experiencing. One of the main problems that they ran into was the size of the data set. Throughout the paper, they suggest several different changes to the algorithms used, and change in data set size, which may help improve the capabilities of the machine.

Discussion 

I don’t know what I was thinking choosing this paper. It was very hard to read. I ended up skimming through it.. I'm sure their research is interesting, but I'm not sure if anyone is going to ever know what they actually did, judging from this paper.