Oct. 10, 2022
MSU researchers to study movement disorders and falls in the elderly
Two researchers from Michigan State University will design and implement scalable wireless systems to track and detect motion in people – assisting in diagnosing movement disorders and alerting caregivers of elderly falls in real time.
Huacheng Zeng, an assistant professor in the Department of Computer Science and Engineering, and Jeffrey Nanzer, an associate professor in the Department of Electrical and Computer Engineering, will use a $450,000 NSF grant for the project, Towards Real-Time Fine-Grained Tracking in Distributed Large-Scale RF Tag Systems.
The project will employ a radio frequency (RF) tag based wireless sensing technology.
“We’ll design and implement a scalable wireless system to track multiple people’s movements,” Zeng explained. “It will help us develop real-life applications to diagnose movement disorders, continuously monitor children's behaviors, and let caregivers know when an elderly patient has fallen.”
Zeng said children and the elderly will have small, lightweight, and low-cost RF tags attached on their clothes.
“The RF tags will look like those used for library books. They are completely passive and need no battery,” Zeng continued. “The tags harvest the radio energy from RF readers and reflect the radio signals back to the readers in specific patterns, which allow RF readers to estimate a tag’s distance and direction.
Nanzer said the wireless tracking system will make it possible to monitor the activities of elderly residents in nursing homes.
“We will be able to preserve their privacy, predict and prevent their possible falls, and guide them to perform doctor-suggested exercises,” Nanzer explained. “It will also enable the continuous monitoring of children’s behaviors and activities in a non-invasive manner, making it possible to conduct data-driven studies of children’s physical and mental development.”
Zeng said they will focus on three complementary research thrusts.
“We will develop fine-grained tag tracking methods for a wireless system by coordinating and synchronizing location-distributed RF readers for precise localization.”
New techniques will maximize the time resolution of tag tracking including signal processing algorithms, sensing protocols, and tag scheduling algorithms.
“The second thrust will develop techniques to enable simultaneous multi-tag tracking similar to the idea of multi-user multiple-input and multiple-output (MU-MIMO) in cellular networks,” Zeng said. “It will significantly improve time resolution, especially in tag-dense scenarios.”
Nanzer noted there will be an additional focus on motion tracking using narrowband harmonic tags and micro-Doppler radar.
“It will advance the design and fabrication of harmonic RF tags and radars for frequency-selective multi-tag operations and explore the performance limits of harmonic tags in tracking applications,” he added.
