Measures of Emotion
Abstract
A tool that could scan a crowded space such as a sporting event or an airport and identify an individual whose identity-based motivations were different than those of the others in the crowd would be immensely useful. Social science theories of emotion and identity indicate this should be possible. The rigor of social science theories predictions about emotion and its operation in social processes and outcomes, however has outstripped our capacity to measure emotions in non-reactive and temporally sensitive ways. Psychophysiological measures of emotion have enabled enormous strides in the scientific understanding of the psychology of emotion. These measures, however, disproportionately require socially invasive technology that prohibit measurement of emotion in ways that do not interfere with ongoing human activities Ð including social interaction. Recent advances in wearable technology have opened up new possibilities for measuring emotion in theoretically informed ways that incorporate information about the social environment, rather than controlling it out. Newer technologies include more affordable, high resolution infrared cameras that can detect changes in blood flow on the face of individuals from a distance and newer headset based EEG measurement devices that capture event related potentials with enough accuracy to successfully capture emotion response, while having an appearance that should minimally interfere with social interaction. The proposed research aims to capitalize on these advances by linking recent advances in technology, computational approaches to measuring emotion, and sociological theory of emotion and identity in order to develop remote, real time measures of emotion that are capable of indexing the features of affective experience most directly tied to social theory and to what we know about the processing of emotion in the brain Ð valence (evaluation), dominance (potency), and arousal (activity). These techniques will be implemented in a study that uses compares two highly unobtrusive remote sensing techniques (facial infrared thermography and automated facial action analysis) to two relatively unobtrusive contact measures (cardiovascular measures and low-cost EEG) and one non-contact but labor intensive measure (tradition hand-coded facial action coding) in their utility to detect individualsÕ group loyalty while observing them watch a contest between their own group and an opposing group.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 07, 2018
- Source ID
- W911NF1710509
Entities
People
- Dawn T. Robinson
Organizations
- Army Contracting Command
- The University of Georgia
- United States Army