Sleep is a one of the most important activity for maintaining the health and well-being of each subject. In order to monitor continuously the quality of sleep of the general population in non-invasively way, we developed an innovative sensorized "smart" mattress (SmartBed). SmartBed is equipped with sensors to detect environmental and subject-related information. In particular, SmartBed is equipped with accelerometers and a sensing textile matrix able to detect the distribution of pressures of a subject laying on the mattress. The purpose of this work is to demonstrate how the sensing textile matrix is not only able to detect how the subject is positioned on the mattress over time, but also it allows to detect other physiological parameters and in particular the subject's respiratory activity. In this work, we show that: (i) the sensing textile matrix allows a precise position detection; (ii) it is possible to extract accurately the respiratory frequency from the sensing textile matrix by using a specifically tailored algorithm. In conclusion, the sensors integrated in SmartBed make possible to detect important information (position and respiratory activity) to determine the quality of a subject's sleep in a robust, accurate and non-invasive way.

Preliminary Assessment of a Smart Mattress for Position and Breathing Sensing

Laurino Marco;
2020

Abstract

Sleep is a one of the most important activity for maintaining the health and well-being of each subject. In order to monitor continuously the quality of sleep of the general population in non-invasively way, we developed an innovative sensorized "smart" mattress (SmartBed). SmartBed is equipped with sensors to detect environmental and subject-related information. In particular, SmartBed is equipped with accelerometers and a sensing textile matrix able to detect the distribution of pressures of a subject laying on the mattress. The purpose of this work is to demonstrate how the sensing textile matrix is not only able to detect how the subject is positioned on the mattress over time, but also it allows to detect other physiological parameters and in particular the subject's respiratory activity. In this work, we show that: (i) the sensing textile matrix allows a precise position detection; (ii) it is possible to extract accurately the respiratory frequency from the sensing textile matrix by using a specifically tailored algorithm. In conclusion, the sensors integrated in SmartBed make possible to detect important information (position and respiratory activity) to determine the quality of a subject's sleep in a robust, accurate and non-invasive way.
2020
Istituto di Fisiologia Clinica - IFC
Breathing monitoring
Sensing mattress
Sleep analysis
Smart textile
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/382486
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