In this webinar sponsored by BIOPAC, experts present applications, best practices, and a demonstration of the integration of eye tracking data with physiological measurements including GSR, HR, and ECG.

On March 8, 2016, InsideScientific hosted a webinar on the integration of eye tracking behavior with physiological monitoring. Speakers Meike Mischo and Arnd Rose from SensoMotoric Instruments and Frazer Findlay from BIOPAC presented user case studies demonstrating new research capabilities made possible by the plug & play integration of eye tracking technology with physiological recording systems.

Dr. Meike Mischo provides an overview of gaze behavior applications and important considerations when integrating eye tracking with physiological measurements, including GSR, heart rate and ECG. Following, Frazer Findlay presents key considerations in recording and analyzing physiological data using a demonstration from a screen-based study. In closing, Dr. Arnd Rose presents a user case study looking at the use of eye tracking and physiological monitoring to evaluate driver stress while operating different assistance systems during driving.

This is an essential webinar for researchers interested in the integration of gaze behavior measurements with physiological monitoring – follow the links below to access key educational points of the webinar.

Dr. Meike Mischo

  • 01:27  Introduction to eye tracking
  • 04:56  Measuring and mapping physiologic function
  • 06:35  Mapping cause and effect relationships with integrated measurements
  • 08:40  How to synchronize eye tracking and physiology recording data streams
  • 12:44  Joint recordings with SensoMotoric Instruments (SMI) and BIOPAC

Frazer Findlay

  • 14:30  Physiological monitoring history
  • 16:27  Demonstration of monitoring physiological data alongside eye tracking
  • 19:28  Identifying stimulus event marks
  • 20:47  Typical eye tracking system set up
  • 22:44  Acknowledge software demonstration
  • 37:27  Data analysis of eye tracking experiment results

Dr. Arnd Rose

  • 43:02  Integrating eye tracking data with physiological measurements in a mobile environment
  • 46:31  Case Study: human-machine interface research for driver assistance system
  • 49:34  Process (preparation, system setup, recording with video, data analysis)
  • 52:27  Video demonstration and study results
  • 55:33  Importance of combining eye tracking and physiological measurement

Q&A

  • 57:16  Regarding the three methods that were discussed for synchronizing data, is one method better than the other? If so, for what situations?
  • 58:56  In the mobile application, what is the maximum  number of physiological signals that can be recorded for a subject? What is the practical amount for using data signals?
  • 1:00:56  What is the youngest age that SMI suggests using eye tracking glasses?
  • 1:01:39  Can the system (SMI eye tracking) be integrated with Functional near-infrared spectroscopy?
  • 1:02:17  Can the viewer region definitions apply to movies rather than images in the SMI software?
  • 1:04:00  Can you import fixation analysis data versus time, to sync physiological data with where the participant was specifically looking at that moment?
  • 1:04:49  What is your opinion on using a head mounted eye tracker as physiological sensor for arousal via pupillometry?
  • 1:06:12  In cardiovascular studies, how would one assess baroreflex sensitivity in human subjects?
  • 1:07:30  In the eyeglasses, is there a built-in video representing what the subject is seeing, or is that video captured on a separate device or integrated some other way?
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SPEAKERS:

ASSOCIATED RESOURCES:

REFERENCES & CITATIONS:

  1. Armstrong, T., & Olatunji, B. O. (2009). What they see is what you get: Eye tracking of attention in the anxiety disorders. American Psychological Association.
  2. Ford, B.Q., Tamir,M., Brunye, T.T., Shirer, W.R., Mahoney, C.R., & Taylor, H.A. (2009) Keeping your eyes on the prize: Anger and visual attention to threats and rewards. Association for Psychological Science, 21(8) 1098-1105. Doi: 10.1177/0956797610375450