Prediction of Elderly Falls Using the Degree of Cyclostationarity of Walk Pressure Signals

There is an increasing interest in developing older adult fall-risk prediction models that can be used as a preventive approach to predict future risk of falling in the elderly community. This study's primary objective is to implement and compare supervised machine-learning methods to classify elderly subjects as fallers or non-fallers. Features used for building the models were extracted from the...