This project will include creating the next version of the iMotions data collector web app (available on GitHub) for accumulating image data for human emotion analysis from anywhere without having the constraints of location, then collecting sample data for examination.
Previous student projects have determined the validity of the software with assorted test subjects with variations on race, facial accessories (glasses), age (wrinkles), physical features, and hair. Emotions available to be analyzed with current version of software include: Joy, Anger, Surprise, Fear, Contempt, Disgust, and Sadness. Additionally, a GSR (Galvanic Skin Reponses System) Shimmer is available for analysis of heart rate and perspiration.
With biometric software and devices now available in the consumer market, results of this project has great potential in the field of geriatrics and telehealth for non-verbal patients. Research shows that facial recognition data can provide a clinicians with much needed urgent information to evaluate pain intensity and source, as well as other syndromes. Combining these biometric technologies will help clinicians diagnose disorders.