Recognition of activities of daily living in Enhanced Living Environments

Enhanced Living Environments consider the recognition of the Activities of Daily Living (ADLs) being performed by users as first step in the aid plans. Some works proved the information about the objects with which a person interacts robustly characterizes the ADL?s identity. However, designing aid plans based on these raw data is a very complicated task, as an expert in both technology and occupational sciences is required. In addition, the plans produced by these experts are not platformindependent, to be closely linked to the hardware characteristics. Therefore, the aim of this paper is to design a two-phase solution capable of acquiring data from users, and of extracting information about the ADL being performed to trigger the execution of the proper aid plans. This solution disengages the technological and occupational domains, so that aid plans could be applied to any environment. Moreover, an experimental validation is conducted in order to validate the proposed technology as a valid solution for ADL recognition