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IIIT-H researchers develop low-cost smart mattress to detect falls, monitor elderly health

Beyond fall detection, the system is designed to monitor sleep patterns, track bed entry and exit times and identify prolonged immobility, a key risk factor for bed sores.

Express News Service

HYDERABAD: For many elderly patients, the real danger is not the fall itself, but the delay in someone realising it has happened. Researchers at the International Institute of Information Technology, Hyderabad (IIIT-H) are working to address this gap with a low-cost, sensor-based smart mattress.

A team led by Prof Aftab Hussain from the Centre for VLSI and Embedded System Technologies is developing a low-cost smart mattress that can detect falls, monitor sleep and provide early warnings of health risks, all without using cameras or wearable devices.

The project has recently received support under the Young Faculty Research Fellowship (YFRF), a selective initiative under the Ministry of Electronics and Information Technology’s Visvesvaraya PhD Scheme.

Falls remain one of the biggest risks for older adults globally, often not because of the fall itself, but due to delayed response. Speaking to TNIE, Prof Aftab Hussain said, “In many cases, help arrives too late, not because care is unavailable, but because no one knows an incident has occurred. To address this gap, we are developing a mattress topper embedded with flexible pressure sensors. These sensors continuously track how a person lies, moves and shifts during sleep. The system can detect falls from the bed and even predict potential risks, such as when a person is lying too close to the edge.”

A researcher at the IIIT-H is developing a low-cost "smart mattress" capable of detecting falls, monitoring sleep, and providing early warnings of health risks

Unlike conventional monitoring systems, the design focuses on privacy and ease. “Camera-based solutions often raise concerns about dignity, while wearable devices depend on consistent usage and can be uncomfortable. The mattress, on the other hand, works passively, requiring no active involvement from the user,” he explained.

Beyond fall detection, the system is designed to monitor sleep patterns, track bed entry and exit times and identify prolonged immobility, a key risk factor for bed sores. The data is analysed using artificial intelligence models trained to distinguish between normal and abnormal movement patterns.

The idea, Aftab Hussain said, emerged from discussions with an elderly healthcare centre in Hyderabad, where patients falling off beds at night was flagged as a key concern. “Since my expertise is in flexible electronics, I proposed using flexible pressure sensors to address this issue. We began conceptualising the solution about two years ago, developed a prototype last year, and after several iterations, the system is now close to deployment. We are preparing for beta testing in a real healthcare setting before moving towards commercialisation,” he said.

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