Challenges and Trends in Multimodal Fall Detection for Healthcare

Chapter 1 Open Source Implementation for Fall Classification and Fall Detection Systems

Chapter 2 Detecting Human Activities Based on a Multimodal Sensor Data Set Using a Bidirectional Long Short-Term Memory Model: A Case Study

Chapter 3 Intelligent Real-Time Multimodal Fall Detection in Fog Infrastructure Using Ensemble Learning

Chapter 4 Wearable Sensors Data-Fusion and Machine-Learning Method for Fall Detection and Activity Recognition

Chapter 6 Approaching Fall Classification Using the UP-Fall Detection Dataset: Analysis and Results from an International Competition

Chapter 7 Classification of Daily Life Activities for Human Fall Detection: A Systematic Review of the Techniques and Approaches

Chapter 8 An Interpretable Machine Learning Model for Human Fall Detection Systems Using Hybrid Intelligent Models

Chapter 10 A Novel Approach for Human Fall Detection and Fall Risk Assessment