• sleep
• ballistocardiogram
• monitoring
• heart rate

Sleeping is very crucial for human’s circadian rhythm, the quality of life in general and the overall well-being of a person. Sleep is a stable and unconscious state and is autonomously controlled by the nervous system, which translates into a periodic, reversible and natural suspension of the conscious life. This thesis concerns the study of some algorithms for the unobtrusive monitoring of the cardiac activity during sleep. The work is part of a research project at IFC Institute of C.N.R. in Pisa, that aims to develop a smart bed that means an intelligent platform that allows to evaluate the quality of sleep in the general population. The basic idea is to develop a platform that allows to have a long-term night-time sleep monitoring using un-obtrusive methods. In fact, to date, the polysomnography (PSG) is currently the primary method used in sleep analysis, but it is expensive, intrusive, complex and it is not suitable for continuous long-term measurements. One of the major unobtrusive method is based on the use of the actigraph. For instance, this thesis work concerns the analysis of some Actigraphy-BCG based algorithms found in the literature at that time. The aim is to compare different algorithms and ways of using the BCG, trying to find the best matching performance with the gold standard. Furthermore, the analysis will provide information on the quality and quantity of slept time.