Extracting Gait Velocity and Stride Length from Surrounding Radio Signals
Name
wigait_chi17.pdf
Description
Accepted version
Size
966.61 KB
Format
Adobe PDF
Checksum (MD5)
44fa2f71af313efaeebe1e8f7854890f
Author(s)
Hsu, Chen-Yu
Liu, Yuchen
Kabelac, Zachary
Hristov, Rumen
Katabi, Dina
Liu, Christine
Date Issued
May 2, 2017
Publisher
ACM
Citation
Hsu, Chen-Yu, Liu, Yuchen, Kabelac, Zachary, Hristov, Rumen, Katabi, Dina et al. 2017. "Extracting Gait Velocity and Stride Length from Surrounding Radio Signals."
Version
Author's final manuscript
Abstract
© 2017 ACM. Gait velocity and stride length are critical health indicators for older adults. A decade of medical research shows that they provide a predictor of future falls, hospitalization, and functional decline among seniors. However, currently these metrics are measured only occasionally during medical visits. Such infrequent measurements hamper the opportunity to detect changes and intervene early in the impairment process. In this paper, we develop a sensor that uses radio signals to continuously measure gait velocity and stride length at home. Our sensor hangs on a wall like a picture frame. It does not require the monitored person to wear or carry a device on her body. Our approach builds on recent advances in wireless systems which have shown that one can locate people based on how their bodies impact the surrounding radio signals. We demonstrate the accuracy of our method by comparing it to the gold standard in clinical tests, and the VICON motion tracking system. Our experience from deploying the sensor in 14 homes indicates comfort with the technology and a high acceptance rate.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
10.1145/3025453.3025937
