This work presents a multi-sensor platform integrating one or more commercial low-cost ambient sensors and one wearable device for the automatic assessment of the physical activity and sedentary time of an aged person. Each sensor node could operate in a stand-alone way or in a multi-sensor approach; in the last case, fuzzy logic data fusion techniques are implemented in a gateway in order to improve the robustness of the estimation of a physiological measure characterizing the level of physical activity and specific parameters for the quantification of a sedentary lifestyle. The automatic assessment was conducted through two main algorithmic steps: (1) recognition of well-defined set of human activities, detected by ambient and wearable sensor nodes, and (2) estimation of a physiological measure, that is (MET)-minutes. The overall accuracy for activity recognition, obtained using simultaneously …