As people age in their 60s and beyond, sleep can turn into a nighttime disappointment. What was once peaceful rest becomes fragmented, unfulfilling, or simply elusive.
For some, the cause is a chronic illness or the medications they take to treat it. Or, it could be linked to depression and anxiety, the double whammy of aging. Also, some disorders, such as sleep apnea and restless leg syndrome, often worsen with age.
It can be a vicious circle. Illness breeds poor sleep which breeds more disease.
Thus, with much of the US population entering their senior years, there is an urgent need to understand more clearly the correlation between sleep and physical and mental illness. And, one key is to find more effective and less invasive ways to monitor older people who hope to stay in their homes.
Dina Katabi helps make this possible. Professor of electrical engineering and computer science at MIT, she and her team have developed a device that uses radio waves to track the quality of sleep (or not) of people. Specifically, it can measure when and for how long a person spends in different stages of sleep, such as light, deep, and REM.
And, unlike more conventional sleep tracking, where a person is hooked up to monitors or has to wear sensors, this innovative approach is built around a housing that can sit, barely perceptible, in a house, a little like a Wi-Fi router.
This is possible because the researchers created an algorithm that allowed the machine to learn to identify different levels of sleep based on the reflection of radio waves in the room where the person is sleeping.
Simply put, the device has learned to recognize a connection between radio signals and different stages of sleep. This was done by showing him numerous examples of sleep stage data from an FDA-approved monitoring device as he tracked radio frequency signals around a room. Because radio waves reflect off a body, even the slightest movement, such as a person’s pulse or breathing, can change the frequency. This month, researchers were granted a patent for this motion tracking system. The algorithm also taught the device to ignore radio signal impairments that are irrelevant, such as those caused by radio wave reflections from inanimate objects in the room.
“After many such instances, the machine learns the radio frequency pattern associated with each sleep phase,” Katabi explains. “At this point, there is no need for more examples. The machine can be taken to a new home and used by a new person. Once it sees the radio frequency pattern, it knows how to map it to the corresponding sleep stage.
That gives the device a big advantage over current sleep tracking methods, says Matt Bianchi, chief of the division of sleep medicine at Massachusetts General Hospital. “It’s not just that it’s home, but more of the ability to perform repeated measurements,” he says. “The quality and quantity of sleep can change from night to night, and this variation can hold important clues that can lead directly to health-related decision-making.
“For example, he adds, the effect of alcohol and body position on sleep apnea is well known, but does not occur in the same way in every person. If we could measure sleep apnea over multiple nights, we could better understand the impact of different behaviors on a person’s sleep and provide more personalized feedback. »
Understanding Parkinson’s disease
Katabi sees another potential benefit to long-term sleep tracking: the ability to better understand the progression of diseases like Parkinson’s disease, which has been shown to have a strong correlation with sleep problems. She notes that many people with a condition called REM sleep behavior disorder (RBD) eventually develop Parkinson’s disease. People with RBD may thrash, flail their arms and legs, or even walk around while still in REM sleep.
“By understanding the relationship between RBD and Parkinson’s disease, we could better understand who might develop Parkinson’s disease and how it progresses,” she says. “It could help develop drugs for Parkinson’s disease.”
Understanding this type of complex relationship between a sleep disorder and a chronic disease, however, requires a long analysis.
“You can’t really understand that unless you watch it over a long period of time,” says Katabi. “Someone who has an REM disorder can take several years to develop Parkinson’s disease. The problem today is that if you want to do longitudinal sleep studies, people would have to go to the hospital or clinic regularly for years. It’s not feasible.
Bianchi explains that while scientists have long been aware of a link between RBD and Parkinson’s disease, they have struggled to determine to what extent the former may precede the latter. The best estimate at this point, Bianchi says, is 10 to 20 years.
“These are incredibly difficult studies to conduct precisely because they take many years and many people to follow,” he says. So Bianchi acknowledges that he’s “very excited” about being able to track key aspects of sleep without a person needing to wear monitoring equipment.
Although Katabi thinks the new device will likely be used for research by pharmaceutical companies and sleep labs before it’s made available to consumers, she sees it as part of a larger goal to make “health conscious” households.
“Despite all the technology in our homes, there is very little to understand health and to be able to detect health emergencies,” she says. “This is especially important for older people who are more likely to have multiple chronic conditions.
“Our vision is something we call ‘invisible’, devices that can sit in the background of your home and can alert a caregiver to health emergencies and also track disease progression,” it adds. she. “That way, a problem can be solved before a person ends up in the emergency room.
“We need to rethink health care. In the same way that computers have changed office work, we need a new system that can cope with the changes that can occur with more and more elderly people living alone. This is where technology can play a very big role.