ABSTRACT
This chapter discusses the convergence of wearable sensor technologies with the traditionally clinical orientated research field of fall assessment and prevention in older adults. Fall detection methods, designed by medical engineering researchers, are generally based on triggering a sensor based system, whether of the wearable sort or within a system installed in a home or residential dwelling. Ariani et al. implemented a proof-of-concept wireless sensor network consisting of passive infrared sensors and pressure mats installed around a home, for fall detection at nighttime. A dichotomy exists in the high-fall risk group, where older adults with the lowest and the highest levels of daily activity are at the greatest risk of a fall, but for different reasons. While the signal parameters used in fall detection have often been derived based on an understanding of the kinematics of falling, fall risk estimation research has been conducted with a little less emphasis on justifying the features and investigating their meanings.
