The goal of this work is the realization of autonomous cyber-physical, microsystems for automated correction of blurred vision using flexible electronic contact lenses. The vision correction system integrates thin variable power lenses with object distance microsensors and computation and control software to continuously produce sharply-focused images in individuals suffering from presbyopia. Presbyopia, or loss of the eye's ability to change focus, is an inevitable and universal age-related condition that affects aging adults, causing blurred images and visual impairment. In 2018, two billion people worldwide were estimated to suffer from presbyopia. The proposed vision correction microsystem operates autonomously while collecting energy from its surrounding environment in order to provide continuous vision correction for an entire day. Realization of such microsystems advances our scientific knowledge of autonomous microsystem engineering for medical applications, ultimately improving the daily lives and well-being of billions of aging adults while reducing the cost of treatment.

The implementation of autonomous microsystems for vision correction requires deep integration of ultrathin state-of-the-art inhomogeneous microtechnologies including variable power liquid-crystal lenses, paper-thin embedded microprocessors and communications circuits with tens of millions of transistors, paper-thin microsensors to detect light level, user orientation and focal distance, and thin photovoltaic cells with power management circuits, all integrated onto a single flexible package that conforms to the surface of the human eye. The system must be able to scavenge power and manage its operation completely autonomously, in the best possible way, in a resource-limited biological environment. Advancements in systems with these characteristics are widely applicable to many future cyber physical systems (CPS) for medical and health monitoring applications. This extremely ambitious project pushes the frontiers of inhomogeneous microtechnology integration to a level that has been repeatedly dreamed of, but never realized before, to produce a highly integrated CPS that can benefit billions of people.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
1932602
Program Officer
Wendy Nilsen
Project Start
Project End
Budget Start
2019-12-01
Budget End
2022-11-30
Support Year
Fiscal Year
2019
Total Cost
$1,199,998
Indirect Cost
Name
University of Utah
Department
Type
DUNS #
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112