Digital transactions have emerged as a dominant force in today’s global commerce sector, empowering businesses and financial institutions like never before. However, at the ...

Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...

Overview This project provides the implementation for the paper, Federated Learning for Hierarchical Fall Detection and Human Activity Recognition, which presents a federated learning framework for ...

Fall incidents are considered as the leading cause of disability and even mortality among older adults. To address this problem, fall detection and prevention fields receive a lot of intention over ...

By monitoring the motion data, a fall detection system (FDS) can detect a fall accident. Recently, wearable sensors–based FDSs have become the mainstream of research, which can be categorized into ...

Algorithm for Learning and Evaluation of Risks in Tumbles (ALERT) is a machine learning project dedicated to enhancing fall detection and prevention strategies. Utilizing advanced algorithms, ALERT ...

We get practical insights into the complexities of machine learning applications, which support the enhanced effectiveness of predictive models in disaster preparedness. The paper not only explains ...

In the current review, we first defined relevant criteria for selecting articles closest to having a machine learning-based solution for fall detection. We identified 15 studies with an operating ...