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An interdisciplinary team of researchers led by Columbia Engineering Associate Professor Xia Zhou has developed PillowSense, a fabric-based sleep-monitoring system. The novel system uses soft sensors to measure heart rate, breathing rate, body movement and sleep posture through natural contact with the sleeper's neck.

Zhou, with the computer science department at Columbia Engineering, worked with experts in computing, engineering and sleep health to develop PillowSense. The system is detailed in "My Pillow Knows My Sleep: Sleep Monitoring with Computational Fabrics in the Pillowcase," presented at the Pervasive and Ubiquitous Computing Conference (UbiComp '26) and received a Distinguished Paper Award at UbiComp in October 2026.

Over 151 nights of at-home testing, PillowSense distinguished seven sleep postures with an F1 score of 88%, a measure of classification performance. The findings suggest a way to collect detailed sleep information without requiring people to wear a device overnight.

Heart rate and breathing measurements provide useful information about sleep, but posture adds another part of the picture. Sleeping position can affect breathing and comfort, while changes in position reveal behavior that vital signs alone do not capture.

"It provides the physical context that makes physiological measurements such as heart rate or breathing more meaningful," Zhou explained.

The project grew out of the group's work on sensing physical activity and motion using everyday fabrics. The researchers wanted to explore whether fabric sensors could also measure physiological signals.

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