MIT wireless device allows remote monitoring of COVID-19 patients
With a large number of doctors and nurses across the world getting infected with COVID-19 after treating patients, researchers at MITs Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a wireless device that allows healthcare professionals to monitor patients remotely.
The device can monitor a patient’s breathing, movement and sleep patterns using wireless signals.
This week, a clinical team in Boston used the device to monitor a COVID-19 patient remotely, CSAIL said on Tuesday.
Developed by MIT professor Dina Katabi and her research group at CSAIL, the device called “Emerald” is a WiFi-like box that analyses the wireless signals in the environment using artificial intelligence (AI) to infer people’s vital signs, sleep, and movement.
After obtaining consent, Heritage Assisted Living in the Boston suburb of Framingham installed Emerald in the patient’s room, where it non-invasively monitors her health and reports the data to her doctor, Ipsit Vahia.
Sitting in his home, Vahia can remotely track the patient’s progress by looking at metrics like breathing and walking speed, CSAIL said.
Specifically, Emerald data showed that the patient’s initial breathing rate had gone down from 23 to 18 breaths per minute -- much closer to the patient’s baseline.
The system also showed that the patient’s sleep quality improved, and that she was able to walk more quickly around her apartment as she recovered.
“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 Vahia, Assistant Professor of Psychiatry at Harvard Medical School.
“Given how Emerald can generate important health data without any patient contact, it could minimise the risk that doctors and nurses will catch the disease from their patients.”
Emerald could also help detect other respiratory problems that would otherwise go unnoticed.
Vahia has used Emerald with a patient who suffers from anxiety and has insomnia problems.
Emerald’s data predicted that the patient had sleep apnea, which was confirmed with follow-up testing, CSAIL said.