Falls are an increasing problem of aging population, both in home-dwelling and institutionalized people. Automatic fall detection systems are a choice in supporting the independent and secure living of the older people. Typically, health technology applications such as fall detection systems are tested in experimental falls of young adults. However, sensitivity and specificity, and acceptability and usability of these systems in real-life conditions in end users should be the ultimate aim. This paper overviews our set of studies on the technology and algorithms for fall detection, from laboratory-based experiments to long-term real-life field tests. The data obtained during the incremental set of studies suggest that automatic accelerometric fall detection systems might offer a tool for improving safety among older people. Additional studies are needed for further improvement of fall detection sensitivity and decreasing the false alarm rate, and for the implementation of the technology to elderly care ICT platforms.
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