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The monitoring of Activities of Daily Living (ADL) is a fundamental task to implement a rigorous remote monitoring of weak users with particular regards to falls. Actually, unintentional falls cause a lot of hospitalizations and could produce serious consequence due to long-lie happenings. The widespread use of smartphones associated with the wide variety of embedded sensors would represent a suitable solution for ADL monitoring. This paper faces the development of fully smartphone based ADL detector which uses advanced signal processing to provide useful and reliable information for the efficient implementation of remote elderly monitoring. The developed strategy allows for ADL classification with sensitivity and specificity features in line with real applications in Ambient Assistive Living (AAL) context.

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