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Ubiquitous Monitoring of Boredom
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Ubiquitous Monitoring of Boredom. H. Estépar 2 , D. Shastri 1 , A. Mandapati 1 , I. Pavlidis 1. (1) Department of Computer Science, University of Houston, Houston, TX 77204. dshastri , amandapa ,,.

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Measurements Technologies

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Measurements technologies

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,,

(2) Department of Electrical and Computer Engineering, University of Puerto Rico, Mayagüez Campus

Mayagüez, Puerto Rico.


Boredom in Context


  • 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


  • 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



Combine symbiotic activities with passive monitoring

  • Mobility

  • - Wireless

  • Portable

  • Minimal obtrusive

Wired sensors


Contact-free sensors

-Thermal imagery

Example of security monitoring


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)]


Thermal camera

Thermal GSR Q-sensor






Time [s]

Time [s]

Validation Results

EAGER Results


  • 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)


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: Mean EDA with activityis greater than without activity

(exception - D006)

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