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A proposal of a fall detection algorithm for a Multidevice Personal Intelligent Platform

In this paper methodological and design issues about the development of a personal platform for the control and processing of data acquired from intelligent biomedical sensors are presented. This platform is designed in the context of a telehealthcare system for the elderly with chronic diseases, and one of its objectives is to monitor and detect fall events. The main feature of the device is its on-line personalization to the patient through adaptive knowledge generation in real-time, which will result in special time execution requirements. As a result a fall detection algorithm proposal is described and analyzed.