AI-Enabled Device Emits Radio Waves to Wirelessly Monitor Sleep Patterns at Home

A laptop-sized system could make it easier to diagnose and study sleep disorders

2 min read
A photo illustration shows a laptop-sized device that monitors sleep patterns mounted to a window in a home office
Photo Illustration: Shichao Yue/MIT

Around 50 million people in the U.S. suffer from sleep disorders. In order for physicians to diagnose these disorders, patients must spend a night in a sleep lab hooked up to electrodes and sensors, which can be unpleasant and nerve-racking.

MIT researchers have now come up with a way to wirelessly capture data on sleep patterns from the comfort of a patient’s home. Their laptop-sized device bounces radio waves off a person, and a smart algorithm analyzes the signals to accurately decode the patient's sleep patterns.

The device could allow experts to monitor someone’s sleep for weeks or months rather than once every few months in an overnight lab. Apart from enabling physicians to diagnose and study sleep disorders, they could also use it to understand how drugs or illnesses such as Parkinson’s disease, Alzheimer’s disease, epilepsy, and depression affect sleep quality.

“Doing this wirelessly in your own bedroom, you could really see the impact of drugs, and progression of diseases by long-term monitoring,” says Dina Katabi, a professor of electrical engineering and computer science at MIT who led the work.

During sleep, we cycle through three different sleep stages: light, deep, and REM. Fitness bands and phone apps use accelerometers to track a person’s sleep patterns, but they don’t produce data on sleep stages that is accurate enough for medical use, Katabi says.

The new RF system combines information on breathing, pulse, and movements to decipher sleep stages with 80 percent accuracy, about the same as lab-based EEG tests. The researchers tested the system on 25 volunteers over 100 nights of sleep. They presented their work at the International Conference on Machine Learning on Aug 9.

The device transmits RF waves at one-thousandth the power of Wi-Fi signals and picks up signals reflected from walls, furniture, and sleeping subjects, whose tiniest movements change the frequency of the reflected signal. The deep neural network algorithm extracts the relevant sleep-related signals from the jumble of reflected signals and translates the data into meaningful sleep stages.

The MIT team has previously used the same radio-based system to measure walking speed and to detect and analyze emotions.

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This CAD Program Can Design New Organisms

Genetic engineers have a powerful new tool to write and edit DNA code

11 min read
A photo showing machinery in a lab

Foundries such as the Edinburgh Genome Foundry assemble fragments of synthetic DNA and send them to labs for testing in cells.

Edinburgh Genome Foundry, University of Edinburgh

In the next decade, medical science may finally advance cures for some of the most complex diseases that plague humanity. Many diseases are caused by mutations in the human genome, which can either be inherited from our parents (such as in cystic fibrosis), or acquired during life, such as most types of cancer. For some of these conditions, medical researchers have identified the exact mutations that lead to disease; but in many more, they're still seeking answers. And without understanding the cause of a problem, it's pretty tough to find a cure.

We believe that a key enabling technology in this quest is a computer-aided design (CAD) program for genome editing, which our organization is launching this week at the Genome Project-write (GP-write) conference.

With this CAD program, medical researchers will be able to quickly design hundreds of different genomes with any combination of mutations and send the genetic code to a company that manufactures strings of DNA. Those fragments of synthesized DNA can then be sent to a foundry for assembly, and finally to a lab where the designed genomes can be tested in cells. Based on how the cells grow, researchers can use the CAD program to iterate with a new batch of redesigned genomes, sharing data for collaborative efforts. Enabling fast redesign of thousands of variants can only be achieved through automation; at that scale, researchers just might identify the combinations of mutations that are causing genetic diseases. This is the first critical R&D step toward finding cures.

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