It has been clear for several weeks that nursing homes and other long-term care settings have been Ground Zero for a significant portion of COVID-19 outbreaks since the pandemic hit our shores. So it’s good new for providers and patients alike that researchers at MIT’s Computer Science & Artificial Intelligence Laboratory (CSAIL) institute have announced that a remote monitoring system they’ve been developing is showing signs of promise.
According to reports, “(t)he system, known as RF-ReID – for ‘radio-frequency re-identification’ – works by analyzing small changes in the wireless signal of an indoor environment,” and CSAIL scientists have recently published a research report that explains how the tool, which can remotely distinguish and the heart rate and respiration patterns of up to 40 unique persons, could provide continuous remote monitoring especially for people living together in group settings such as nursing homes.
"The new invention allows us to identify measurements from the same person, but without collecting identifying private information about them, including their appearance," explained Prof. Dina Katabi, director of the MIT Wireless Center, who has been the lead researcher on the technology for years.
She noted that while there are other methods for tracking measurements from the same person over time – surveillance cameras, wearable devices – “those approaches are impractical and don’t offer the same privacy guarantees as RF-ReID.”
Lijie Fan and Tianhong Li, MIT graduate students who co-developed RF-ReID, say they plan to adapt the system to detect and track health problems among high risk populations. They developed the project alongside visiting scholar Rongyao Fang, master’s student Rumen Hristov and postdoctoral associate Yuan Yuan.
The team used the system in 19 different retirement communities, and found that, after training it on more than 20 people, it could look at a new person and re-identify them after barely 10 seconds of physical activity.
That tool is able to re-identify people using a range of qualities it infers from radio signals: body size, walking speed, and even walking style.
Earlier tests on the device, dubbed “Emerald,” had demonstrated its capacity to monitor COVID-19 patients remotely, thus minimizing provider exposure to the virus.
“When doctors have to interact directly with patients to conduct exams or monitor vital signs, each step along the way represents an increased risk that they will get infected,” said Ipsit Vahia, ND, an assistant professor of psychiatry at Harvard Medical School. “Given how Emerald can generate important health data without any patient contact, it could minimize the risk that doctors and nurses will catch the disease from their patients.”