The results show the theory behind the Emotion mouse work is fundamentally sound. The physiological measurements were correlated to emotions using a correlational model. The model is derived from a calibration process in which a baseline attribute-to-emotion correlation is rendered based on statistical analysis of calibration signals generated by users having emotions that are measured or otherwise known at calibration time.
Now that we have proven the method, the next step is to improve the hardware. Instead of using cumbersome multimeters to gather information about the user, it will be better to use smaller and less intrusive units. We plan to improve our infrared pulse detector which can be placed inside the body of the mouse. Also, a framework for the user modeling needs to be develop in order to correctly handle all of the information after it has been gathered.
There are other possible applications for the Emotion technology other than just increased productivity for a desktop computer user. Other domains such as entertainment, health and the communications and the automobile industry could find this technology useful for other purposes.
Many thanks to David Koons, Florian Vogt, Frank Hoffmann, Steven Ihde and Rajat Paharia for their help on early versions of the software and hardware. Also, thanks to the BlueEyes team for their support.
Ekman, P. and Rosenberg, E. (Eds.) ( 1997). What the Face Reveals: Basic and Applied Studies of Spontaneous Expression Using the Facial Action Coding System (FACS). Oxford University Press: New York.
Dryer, D. C. ( 1993). "Multidimensional and Discriminant Function Analyses of Affective State Data". Stanford University, unpublished manuscript.
Dryer, D. C. ( 1999). "Getting personal with computers: How to design personalities for agents". Applied Artificial Intelligence, 13, 273-295.
Dryer, D. C., and Horowitz, L. M. ( 1997). "When do opposites attract? Interpersonal complementarity versus similarity". Journal of Personality and Social Psychology, 72, 592-603.
Johnson, R. C. ( 1999). "Computer Program Recognizes Facial Expressions". EE Times www.eetimes.com, April 5.
Picard, R. ( 1997). Affective Computing. MIT Press: Cambridge.