Dynamic Fall Risk Assessment


Inquiry: What if we could predict a fall before it happens?


Wearable fall risk assessment & prediction system


Third Technology Capital Investors

Research Partner

Arizona State University, MORE Foundation

Principle Investigator

Dr. Thurmon Lockhart

Research Objective:

Prototyping Testing Validation



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ccidents are among the leading causes of death for adults 65 and older in the United States. In 2016, accidental falls caused 974 deaths, 14,384 inpatient hospitalizations and 42,808 emergency department visits — contributing to the U.S. projection for associated costs at around $65B.

Utilizing Dr. Lockhart’s National Science Foundation sponsored research, this project is developing a smartphone application that will predict if the patient is at risk for falling.  This product will allow fall risk assessments to escape expensive laboratories and be used in clinical settings.

Through the use of cloud based machine learning, the data from these clinical assessments will inform physicians about fall risks for future patients.

Which came first:

The chicken or

The egg-shaped, edible sensor?

Read more WearTech News, this sentence goes onto two lines to engage the reader’s curiosity.

Inside Innovation

Innovator's Journey:

Fall Prediction

Go inside Thurmon Lockhart's journey developing the Lockhart Monitor.

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