Sensor-Based Gait Analysis and Machine Learning for Predictive Fall Risk Assessment in Adults

The need for fall prediction and prevention measures arose from the increasing global ageing population’s increased incidence of falls among the elderly. The combination of Internet of Things (IoT) devices and machine learning algorithms is becoming more and more prevalent in these methods. These algorithms are able to identify changes in gait patterns based on data gathered from many sensors, such as accelerometers and gyroscopes, providing early warning signs of approaching falls.