Fall algorithm development using kinematic parameters measured from simulated falls performed in a quasi-realistic environment using accelerometry

This study aims to determine the optimal temporal, angular and acceleration parameters and thresholds for an accelerometer based, chest-worn, fall detection algorithm. In total, 10 healthy male subjects performed 14 different fall types, 3 times by each. The falls were performed onto in a quasi-realistic environment consisting of mats of a minimum thickness. Optimum parameters for; t_falling: time-to-fall, θ_max: max-angle, t_θmax : max-angle-time, t_RTStanding : Return-to-standing-time and t_lying : lying-time were determined using a data set consisting of a total of 420 falls.