About the Lab
Dr. Dinko Bačić
Lab Founder and Principal Investigator
Dr. Dinko Bačić is an Assistant Professor of Information Systems at Loyola University Chicago's Quinlan School of Business. His research interests include Business Information Visualization, Human-Computer Interaction, UX, Biometrics, Cognition, NeuroIS, BI & Analytics, and IS pedagogy. He has papers published in leading information systems and interdisciplinary outlets such as Decision Support Systems, Communications of the AIS, AIS Transactions on HCI, Behaviour and Information Technology, Journal of Information Systems Education, and Leonardo. Dr. Bačić currently teaches undergraduate (Data Visualization & BI (INFS360), Business Information Systems (INFS247), Analytical Decision Making (BH343)) and graduate (Application of Visualizations (INFS797), Business Requirements Analysis (INF485)) courses.
He is the founder and principal researcher in the User Experience & Biometrics Lab. Dr. Bačić is a recipient of Quinlan's Graduate Teaching Award and has been nominated multiple times for the Peter Hans Kolvenbach Award for Engaged Teaching and the St. Ignatius of Loyola Excellence in Teaching Award. He currently serves as co-chair of the Human-Computer Interaction Conference (held annually in Opatija, Croatia). He has more than fifteen years of corporate and consulting experience in business intelligence, finance, project management, and HR.
Biometric Technology
Facial Expression Analysis:
Using a monitor and camera to establish identifier points on the face, this technology can measure 7 basic emotions, valence, 19 emotion channels, 33 facial landmarks, head orientation, interocular distance, and engagement of the participant. The Facial Action Coding System (FACS) is a classification system of facial expressions used within this technology.
Eye Tracking:
Using a high-resolution camera on a lab monitor or laptop, Pupil Center Corneal Reflection (PCCR) technology tracks the pupil center, along with where light reflects from the cornea, to track gaze detection. Additionally, it can be used to assess many other metrics to determine focus, attention, and engagement toward a stimuli.
Galvanic Skin Response:
Attached to the wrist and fingers, this technology measures autonomic nervous system responses, such as a participant's arousal, stress, excitement, emotional engagement, and heart rate. The participant's skin conductance, or sweat, is coined as this Galvanic Skin Response (GSR).
iMotions Software
Create complex research studies
Utilize biometric technology
Collect & analyze data
Create useful data visualizations
Design surveys to collect subjective data