Purpose Fall accidents can cause casualties and economic losses in the construction
industry. Fall portents, such as loss of balance (LOB) and sudden sways, can result in fatal …

Falls are the leading cause (eg, 30–35%) of work-related fatalities during construction.
However, conventional sensing approaches to recognizing workers' fall-related movements …

Theabnormal behavior detection is the vital for evaluation of daily-life health status of the
patient with cognitive impairment. Previous studies about abnormal behavior detection …

Due to the ever growing population of elderly people, there is a dramatic increase in fall
accidents. Currently, multiple ideas exist to prevent the elderly from falling, by means of …

Abstract Human Activity Recognition (HAR), based on sensor devices and the Internet of
Things (IoT), attracted many researchers since it has diversified applications in health …

The increase in the proportion of elderly in Europe brings with it certain challenges that
society needs to address, such as custodial care. We propose a scalable, easily modulated …

In the realm of sustainable IoT and AI applications for the well-being of elderly individuals
living alone in their homes, falls can have severe consequences. These consequences …

Falls represent a significant public health concern, particularly concerning vulnerable
populations such as older adults. Accurate detection and classification of falls are critical for …

Automated human fall detection is an essential area of research due to its health
implications in day‐to‐day life. Detecting and timely reporting of human falls may lead to …

Featured Application In this study, a wearable system that can recognize human posture
was developed. By using long short-term memory-based recurrent neural network (LSTM …