NIT Rourkela develops multi-sensor AI system for accurate patient sleep posture detection

Rourkela (Odisha):  Researchers at National Institute of Technology Rourkela (NIT Rourkela), Odisha, have developed an AI-enabled system that can track human sleep postures. This is useful in healthcare settings, as it provides a non-intrusive way to monitor patients while maintaining their privacy, even when they are covered with a blanket.

The findings of this research have been published in the IEEE Sensors Journal. The paper is co-authored by Professor Saptarshi Chatterjee, Assistant Professor, department of electronics and communication engineering, along with his B.Tech student Shiladitya Mondal at NIT Rourkela, and Dr. Debangshu Dey, Assistant Professor, Department of Electrical Engineering, Jadavpur University.

Studies from around the world show that poor sleeping posture can cause long-term health conditions by putting sustained, uneven pressure on the spine, joints, and nerves for hours at a time. Even for a physically active person, this can lead to chronic musculoskeletal pain, spinal degeneration, obstructive sleep apnea, nerve damage, poor digestion and acid reflux, and arthritis, among others. For bedridden patients, poor posture can cause serious complications such as pressure ulcers or bedsores.

Currently, patient posture monitoring is mostly done manually, which can be inconsistent and prone to human error. Wearable sensors are another option, but they are often expensive and uncomfortable for patients. Camera-based systems also exist, but they face challenges like low lighting, obstruction due to blankets, and privacy concerns, making them less suitable.

To overcome these issues, Prof. Saptarshi Chatterjee and his team developed an AI-based system that uses three types of sensors: The sensors include a long-wave infrared imaging sensor that tracks body heat to monitor sleeping posture without capturing visual images, even under a blanket, a depth sensor that captures body shape and posture, a pressure sensor that measures how body weight is distributed on the bed.

To process the data from these sensors, the team developed a generative AI model to create a clear representation of the human body, along with a graph-based neural network to identify the postures of different body joints.

Speaking about the developed system, Prof. Saptarshi Chatterjee, Assistant Professor, Department of Electronics and Communication Engineering, NIT Rourkela, said, “Our system leverages generative AI along with a fusion technique combining low-wave infrared, depth, and pressure map data to detect sleeping postures without directly using RGB images. The model performs effectively even under challenging conditions such as low lighting and varying types of coverings.”