  We present a glasses type wearable device to detect emotions from a human
face in an unobtrusive manner. The device is designed to gather multi channel
responses from the user face naturally and continuously while the user is
wearing it. The multi channel responses include physiological responses of the
facial muscles and organs based on electrodermal activity (EDA) and
photoplethysmogram. We conducted experiments to determine the optimal positions
of EDA sensors on the wearable device because EDA signal quality is very
sensitive to the sensing position. In addition to the physiological data, the
device can capture the image region representing local facial expressions
around the left eye via a built in camera. In this study, we developed and
validated an algorithm to recognize emotions using multi channel responses
obtained from the device. The results show that the emotion recognition
algorithm using only local facial expressions has an accuracy of 78 percent at
classifying emotions. Using multi channel data, this accuracy was increased by
10.1 percent. This unobtrusive wearable system with facial multi channel
responses is very useful for monitoring a user emotions in daily life, which
has a huge potential for use in the healthcare industry.
