Human falls are one of the leading causes of fatal unintentional injuries worldwide. Falls
result in a direct financial cost to health systems, and indirectly, to society's productivity …

Fall events among older adults are a serious concern, having an impact on their health and
well-being. The development of the Internet of Things (IoT) over the last years has led to the …

This paper presents a framework based on multilayer bi-LSTM network (bidirectional Long
Short-Term Memory) for multimodal sensor fusion to sense and classify daily activities' …

This book presents challenging issues and current trends for designing human fall detection
and classification systems, as well as healthcare technologies, using multimodal …

Falls are one of the most common causes of injury among the elderly. As a result, fall
detection has received in the last decade considerable attention from both academia and …

This paper presents a methodology based on multimodal sensors to configure a simple,
comfortable and fast fall detection and human activity recognition system that can be easily …

Human fall detection plays a vital role in monitoring senior citizens safely while being alone.
In recent works, vision-based techniques provide favorable and effective results. In this …

Human falls are common source of injury among the elderly, because often the elderly
person is injured and cannot call for help. In the literature this is addressed by various fall …

Fall detection can improve the security and safety of older people and alert when fall occurs.
Fall detection systems are mainly based on wearable sensors, ambient sensors, and vision …

Accurately predicting fall detection from wearable sensor data has many implications.
Detecting falls and other activities from wearable data provide a method by which it assists …