Ubiquitous Monitoring of Boredom: Using Q-Sensor for Physiological State Assessment

1. Ubiquitous Monitoring of Boredom H. Estépar2, D. Shastri1, A. Mandapati1, I. Pavlidis1 (1) Department of Computer Science, University of Houston, Houston, TX 77204. dshastri, amandapa, ipavlidis@uh.edu, (2) Department of Electrical and Computer Engineering, University of Puerto Rico, Mayagüez Campus Mayagüez, Puerto Rico. henry.estepar@upr.edu Application Boredom in Context Objective • To use Q-sensor to quantify the physiological state of boredom and compare it withrespect to GSR and facial thermal data • 1. Lowers heart rate and respiration rate (Similar to those experienced in sleepiness) • 2. Changes electro dermal activity (EDA) Subjects under boredom tend to be more susceptive to distractions . Classical example of boredom: The work of security guards Motivation • Problem: • Need to stare at rarely interesting • video feeds • More susceptible to distractions • Any mistake can cost a lot This highly accurate technology for measuring, temperature, EDA, and motion intensity (X,Y and Z co-ordinates) has never been used with such an objective. The experimental results show that monitoring of the Q-sensor channels yields similar detecting power to GSR’s. and thermal imaging. Wearable sensors - Q-Sensor Track boredom through physiological variables Quantify physiological responses Measurements Technologies Advantages Solution: Combine symbiotic activities with passive monitoring • Mobility • - Wireless • Portable • Minimal obtrusive Wired sensors - ECG, EEG, GSR Contact-free sensors -Thermal imagery Example of security monitoring Validation EAGER Experiment 1. Experimental Design 1. Experiment Design 2. Data Analysis Symbiotic Activities Includes 2 wand games, 2 puzzle games, and 1 web browser. • The experiment lasts 4 hours (10 sessions) • The subject is asked to note suspicious • behavior they see. • 5 sessions of traditional monitoring, • and five with symbiotic activities. • The subject is monitored by thermal • imaging and contact sensors • The experiment lasts 4 minutes • The subject is asked to count circles that appear randomly on the monitor • The subject is monitored by thermal imaging and contact sensors • After every minute an auditory startle is delivered • Experimental Timeline • The experiment ends about 1 min after the delivery of the third startle Step1: Extract thermalsignal from maxillaryregion, GSRand Q-sensorsignal Step2: Down sample the collected data from signals Step3:Normalize the signals Step4: Reduce Q-sensor noise Step5: Perform data analysis [signal correlation, Even Peak Time (ETP) and Even Peak Intensity (EPI)] Browser Thermal camera Thermal GSR Q-sensor Mouse Q-sensor GSR Keyboard Subject Time [s] Time [s] Validation Results EAGER Results Conclusion • Q-sensor can be used effectively to measure temperature, EDA and motion intensity of the psychological state of boredom. • Subjects presented higher mean EDA and were more active when exposed to a symbiotic activity. • The obtained signal from Q-sensor is similar compared with those of GSR and thermal. Even Peak Time (EPT) Even Peak Intensity (EPI) Acknowledgement This research was sponsored by NSF grant number SCI-0453498. Additional thanks to the UH Department of Computer Science, College of Natural Sciences and Mathematics, Dean of Graduate and Professional Studies, VP for Research, and the Provost’s Office. Summary: Summary: Mean EDA with activityis greater than without activity (exception - D006)