A lightweight wearable electrode array for electrooculography

Tracking eye movement is integral for constructing virtual reality headsets, and in the healthcare sector, eye movement tracking is useful for diagnosing sleep disorders. Current iterations of commercial eye trackers mainly rely on visually tracking the wearer’s retina using head-mounted cameras. This approach suffers from many analytical limitations, in addition to the fact that the resulting headsets are heavy, cumbersome, and constricting.

Aside from cameras, another method to track eye movement is electrooculography (EoG), in which the electric pulses created by the seven extraocular muscles are detected by a skin-mounted electrode. While EoG is the most sensitive and error-free approach to track eye motion, a fully-integrated and portable EoG headset with five electrode leads is not known.

Here, Professors Trisha Andrew and Deepak Ganesan create a lightweight garment that can record EoG signals and, therefore, track the eye motions of the wearer. The PIs decorate a lightweight molded-foam sleeping mask with dry electrodes, and integrate a power source and processing circuit onto the headband of the sleep mask. This creates a fully-integrated and sensitive eye tracking system that can be used to create next-generation VR headsets and track eye movement in patients suffering from sleep disorders.

TECHNOLOGY DESCRIPTION

ADVANTAGES

•      Lightweight, comfortable

•      Machine washable

•      Integrated fabric electrodes – completely novel

•      Integrated small form factor signal processing PCB

•      Five eye tracking leads vs. 1-2 found in commercial trackers

PRODUCT OPPORTUNITIES

•      Augmented reality/virtual reality (AR/VR) headsets

•      Smart sleep masks for sleep monitoring

ABOUT THE INVENTORS

Trisha L. Andrew is an Associate Professor of Chemistry and Materials Engineering at the University of Massachusetts Amherst. She started her independent career in 2012 at the University of Wisconsin-Madison, where she was an Assistant Professor of Chemistry and Electrical Engineering. She received her education at the University of Washington (B.S.) and at the Massachusetts Institute of Technology (Ph.D.). Trisha is the Director of the Wearable Electronics Lab at the University of Massachusetts Amherst. The WELab strives to produce emergent electronic technologies on unconventional substrates by using organic materials to achieve unmatched control over processing conditions, device dimensions and the spin of charge carriers. Trisha is a David and Lucille Packard Foundation Fellow, and an Air Force Young Investigator and 3M Nontenured Faculty Award winner.

Deepak Ganesan is a Professor in the Department of Computer Science at UMass Amherst. His research focuses on ultra-low power wireless communication via backscatter, novel platforms and algorithms for mobile and wearable health sensing, learning and inference on multi-modal sensor data, and micro-powered sensors. Dr. Ganesan leads the UMass Sensors Research Group.

AVAILABILITY:

Available for Licensing and/or Sponsored Research

DOCKET:

UMA 19-024

PATENT STATUS:

Patent Pending

NON-CONFIDENTIAL INVENTION DISCLOSURE

LEAD INVENTOR:

Trisha Andrew and Deepak Ganesan

CONTACT:

Tracking eye movement is integral for constructing virtual reality headsets, and in the healthcare sector, eye movement tracking is useful for diagnosing sleep disorders. Current iterations of commercial eye trackers mainly rely on visually tracking the wearer’s retina using head-mounted cameras. This approach suffers from many analytical limitations, in addition to the fact that the resulting headsets are heavy, cumbersome, and constricting.

Aside from cameras, another method to track eye movement is electrooculography (EoG), in which the electric pulses created by the seven extraocular muscles are detected by a skin-mounted electrode. While EoG is the most sensitive and error-free approach to track eye motion, a fully-integrated and portable EoG headset with five electrode leads is not known.

Here, Professors Trisha Andrew and Deepak Ganesan create a lightweight garment that can record EoG signals and, therefore, track the eye motions of the wearer. The PIs decorate a lightweight molded-foam sleeping mask with dry electrodes, and integrate a power source and processing circuit onto the headband of the sleep mask. This creates a fully-integrated and sensitive eye tracking system that can be used to create next-generation VR headsets and track eye movement in patients suffering from sleep disorders.