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Reimagining Sleep Monitoring with AI and Wearable Tech

Sleep is vital for our health, helping us recharge, heal, fight off illness, and keep our brains working properly. But understanding sleep in detail, especially for diagnosing disorders, usually requires a complex and expensive lab test called polysomnography (PSG). This involves hooking people up to multiple sensors to track brain waves, eye movement, muscle activity, and heart rate, followed by hours of expert analysis.

Because PSG is so intrusive and costly, it’s not practical for studying sleep across large groups of people. That’s where wearable technology comes in. Devices like smartwatches and headbands can track movement, heart rate, and even brain activity in a much simpler way. While they’re not yet as accurate as lab tests, they’re affordable and widely accessible, making them ideal for large-scale sleep research.

In a new collaboration between the University of Warwick and Fudan University, researchers are combining expertise in computer science, engineering, and sleep science to build smarter sleep monitoring tools using AI. By analysing data from wearables like accelerometers, heart rate sensors, and single-channel EEG, they aim to create reliable models that can detect sleep stages and patterns more accurately.

The team will develop advanced AI systems that can align and combine data from different sources, learn general patterns across diverse populations, and separate sleep-related signals from other noise. They’re also building a user-friendly platform to help researchers and doctors better understand sleep data and discover new health insights.

This project lays the foundation for future breakthroughs in sleep science, with the potential to improve public health, support better sleep treatments, and make sleep monitoring more accessible to everyone.

Dr Yu Guan

Department of Computer Science

University of Warwick

Dr Chen Chen

Human Phenome Institute

Fudan University

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