Fall Risk Prediction Using Wearable Wireless Sensors

Authors

Thurmon Lockhart, Virginia Polytechnic Institute and State University
Chris Frame, Virginia Polytechnic Institute and State University
Rahul Soangra, Chapman UniversityFollow
John Lach, University of Virginia

Document Type

Conference Proceeding

Publication Date

5-28-2014

Abstract

Wearable wireless sensors and nonlinear dynamics identify postural characteristics relevant to balance control and dynamic stability, revealing predictive risk of falls among older adults.

Comments

This article was originally published in Sensing and Measurement in 2014. DOI: 10.1117/2.1201405.005437

Recommended Citation

Lockhart T, Frame C, Soangra R, Lach J. Fall risk prediction using wearable wireless sensors. Sensing & Measurement. 2014, May 28. doi: 10.1117/2.1201405.005437

Copyright

SPIE