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Eustressed or Distressed? Combining Physiology with Observation in User Studies. Avinash Wesley Dr. Peggy Lindner (Co-Advisor) Dr. Ioannis Pavlidis (Advisor). Stress Signs. Introduction Methods Results and Discussion Acknowledgements. Stress Mechanism Motivation Background.

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eustressed or distressed combining physiology with observation in user studies

Eustressed or Distressed?Combining Physiology withObservation in User Studies

  • Avinash Wesley
  • Dr. Peggy Lindner (Co-Advisor)
  • Dr. IoannisPavlidis (Advisor)
stress signs
Stress Signs
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Stress Mechanism
  • Motivation
  • Background
  • Peripheral Physiological Measurement of Stress
    • Adrenergic response
      • Elevates heart rate, respiration rate, and blood pressure
    • Cholinergic response
      • Activates sweat glands on fingers and the perinasal area
physiology and observation
Physiology and Observation
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Stress Mechanism
  • Motivation
  • Background
  • Perspiratory response are
    • sympathetic in nature
    • Non-specific to positive or negative arousal

Distress

Eustress

emotions vs performance
Emotions vs. Performance
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Stress Mechanism
  • Motivation
  • Background
  • An important goal in user studies: Study the role of emotions on human performance
  • Emotions can be quantified via physiological response
  • Physiological responses can be disambiguated via observation

Performance

HIGH

Optimal

Alertness

Anxiety

Disorganization

Sleep

LOW

MEDIUM

HIGH

Arousal

perspiration signal and observation
Perspiration Signal and Observation
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Stress Mechanism
  • Motivation
  • Background
  • Physiology
    • Perspiration extraction method

in the Thermal Imagery [1]

  • Observational Annotation
    • Traditional done in the Visual Imagery
      • Manual

Courtesy of Science channel

[1] D. Shastri, A. Merla, P. Tsiamyrtzis, and I. Pavlidis. Imaging facial signs of neurophysiological responses. IEEETransactions on Biomedical Engineering, 56(2):477–484, 2009.

region tracking
Region Tracking
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Facial Expression Recognition
  • Field Study
  • Seven anatomical regions tracked over time by a dynamic template update tracker [2]

[2] Y. Zhou, P. Tsiamyrtzis, and I. Pavlidis. Tissue tracking in thermo-physiological imagery through spatio-temporal smoothing. Proc. of the 12th Int. Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2009),5762:1092–1099, 2009.

pattern classification
Pattern Classification
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Facial Expression Recognition
  • Field Study
  • Feature Vector
  • Classifier
    • Classify five action units (AU1+2, 4, 9, 10, and 12)
    • Multilayer Perceptron
    • 10-fold Cross Validation

d(x,5): Euclidean distance between ROI-x and 5, (x 5)

AU 1+2

Inner + Outer Eyebrow Raise

surgical training
Surgical Training
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Facial Expression Recognition
  • Field Study
  • Surgeon Pool (n=17)
    • Novices
    • Experienced
  • Tasks
    • Running string (Task-1)
    • Pattern cut (Task-2)
    • Intracorporeal suture (Task-3)
  • Dataset: 977 Thermal Clips
validation results
Validation Results
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Quantitative Analysis
  • Qualitative Analysis
  • Conclusions
  • Using Thermal Imagery
    • 244 Facial Expressions
    • Ground Truth via Visual annotation
    • Method Accuracy 81.55%

*

Confusion matrix

* Use of visual images instead of thermal images for display purpose only

results from the field study
Results From The Field Study
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Quantitative Analysis
  • Qualitative Analysis
  • Conclusions
  • Distress is inversely related to experience
    • EN (Perinasal perspiratory signal on portions of negative emotions)

Novice Experienced

example visualizations
Example Visualizations
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Quantitative Analysis
  • Qualitative Analysis
  • Conclusions

Eustress Distress

conclusions
Conclusions
  • Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Quantitative Analysis
  • Qualitative Analysis
  • Conclusions
  • The proposed method is
    • Comprehensive (quantitative and qualitative)
    • Economical (single imaging modality with no labor)
  • Conducted a study design that is applicable to a broad class of Human Machine Interaction
  • Future Work
    • Expand the facial expression set
    • Apply the method to more field studies
      • Detection of pain onset-offset
slide13
Introduction
  • Methods
  • Results and Discussion
  • Acknowledgements
  • Support provided by NSF award # IIS-0812526
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