The COVID-19 threat to healthcare workers has a double whammy. Doctors, nurses, and other care workers are exposed to infection every day they work. The personal health cost of medical professionals putting themselves in harm’s way is the first hit. The potential knock-out punch to our system is a fact we now face daily; as our health care workers fall sick and out of the workforce, the U.S. medical system falters. When hospitals are overwhelmed, the medical system fails.
Remedying the gut-level threat and national embarrassment of insufficient supplies of protective garments and gear for medical workers would be a first major step on the path of protecting these vital warriors. Care solutions that reduce the threat of infectious exposure are a second protective level for clinical and support staff.
Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) developed a device that remotely monitors the movement, breathing, and sleep patterns of multiple people. The Emerald is a wall-mounted device that is currently being tested in multiple locations in the Boston area.
The device emits WiFi-like radio waves, and then uses artificial intelligence algorithms to analyze the returning signals. This information can indicate the vital signs, sleep, and movement of multiple subjects in a single location. The Emerald sends the results of its analysis to a physician who can monitor patients’ status and progress. According to CSAIL, the Emerald’s sleep stage analysis is 80% as accurate as analysis by sleep specialists using EEG data.
Remote monitoring devices such as Emerald have a double payoff. In addition to reducing physicians’ contact with possibly contagious patients, Emerald also has the potential to expand care to more people. If doctors were confident in remote monitoring accuracy, patients who are not acutely ill could stay in their own homes; this could lighten the demand for hospital beds and enable the system to care for more people. The system could also be helpful as a remote monitor for aging-in-place applications.
