Stumbling Prediction Method Using an Inertial Sensor to Prevent Falls During Walking

In modern society, where the population is aging, fall prevention is an extremely important issue for extending healthy life expectancy, preventing nursing care, and reducing the economic burden on families. However, while numerous studies have been conducted on fall risk estimation, fall motion detection, and fall occurrence detection, studies on fall prediction remain limited. This is because it requires multiple sensors and wearable devices, which lacks practicality. In this study, we investigated the possibility of predicting stumbling during the initial swing phase for the purpose of preventing falls during walking in elderly people. First, using Simscape Multibody, one of the toolboxes of MATLAB/Simulink, we developed a total of 36 models by combining six leg models and six walking models. Next, we attached one inertial sensor to the toe in the simulation and analyzed and compared the data. As a result, it was confirmed that stumbling can be predicted based on the positive or negative slope of angular acceleration in the first half of the initial swing phase just prior to stumbling.