Sensor-mesh-based system with application on sleep study

Description

The process of restoring our body and brain from fatigue is directly depending on the quality of sleep. It can be determined from the report of the sleep study results. Classification of sleep stages is the first step of this study and this includes the measurement of biovital data and its further processing. In this work, the sleep analysis system is based on a hardware sensor net, namely a grid of 24 pressure sensors, supporting sleep phase recognition. In com-parison to the leading standard, which is polysomnography, the proposed ap-proach is a non-invasive system. It recognises respiration and body movement with only one type of low-cost pressure sensors forming a mesh architecture. The nodes implement as a series of pressure sensors connected to a low-power and performant microcontroller. All nodes are connected via a system wide bus with address arbitration. The embedded processor is the mesh network endpoint that enables network configuration, storing and pre-processing of the data, external data access and visualization. The system was tested by executing experiments recording the sleep of differ-ent healthy young subjects. The results obtained have indicated the potential to detect breathing rate and body movement. A major difference of this system in comparison to other approaches is the innovative way to place the sensors under the mattress. This characteristic facilitates the continuous using of the system without any influence on the common sleep process.

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