MIT researchers have developed a wireless, private way to monitor a person's sleep postures - whether snoozing on their back, stomach, or sides - using reflected radio signals from a small device mounted on a bedroom wall.
The device, called BodyCompass, is the first home-ready, radio-frequency-based system to provide accurate sleep data without cameras or sensors attached to the body, according to Shichao Yue. The PhD student has used wireless sensing to study sleep stages and insomnia for several years.
In the future, people might also use BodyCompass to keep track of their own sleep habits or to monitor infant sleeping.
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"We thought sleep posture could be another impactful application of our system" for medical monitoring, says Yue, who worked on the project under the supervision of Prof. Dina Katabi in the MIT Computer Science and Artificial Intelligence Laboratory. Studies show that stomach sleeping increases the risk of sudden death in people with epilepsy, he notes, and sleep posture could also be used to measure the progression of Parkinson's disease as the condition robs a person of the ability to turn over in bed.
Other authors on paper, published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, include graduate students Yuzhe Yang and Hao Wang, and Katabi Lab affiliate Hariharan Rahul. Katabi is the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT.
BodyCompass works by analyzing the reflection of radio signals as they bounce off objects in a room, including the human body. Similar to a Wi-Fi router attached to the bedroom wall, the device sends and collects these signals as they return through multiple paths. The researchers then map the paths of these signals, working backward from the reflections to determine the body's posture.
For this to work, however, the scientists needed a way to figure out which of the signals were bouncing off the sleeper's body, and not bouncing off the mattress or a nightstand or an overhead fan. Yue and his colleagues realized that their past work in deciphering breathing patterns from radio signals could solve the problem.
Signals that bounce off a person's chest and belly are uniquely modulated by breathing, they concluded. Once that breathing signal was identified as a way to "tag" reflections coming from the body, the researchers could analyze those reflections compared to the position of the device to determine how the person was lying in bed. (If a person was lying on her back, for instance, strong radio waves bouncing off her chest would be directed at the ceiling and then to the device on the wall.) "Identifying breathing as coding helped us to separate signals from the body from environmental reflections, allowing us to track where informative reflections are," Yue says.
Reflections from the body are then analyzed by a customized neural network to infer how the body is angled in sleep. Because the neural network defines sleep postures according to angles, the device can distinguish between a sleeper lying on the right side from one who has merely tilted slightly to the right. This kind of fine-grained analysis would be especially important for epilepsy patients for whom sleeping in a prone position is correlated with sudden unexpected death, Yue says.
MEDICA-tradefair.com; Source: Massachusetts Institute of Technology