Detecting falls with wearable sensors using machine learning techniques
AT Özdemir, B Barshan - Sensors, 2014 - mdpi.com
Falls are a serious public health problem and possibly life threatening for people in fall risk
groups. We develop an automated fall detection system with wearable motion sensor units …
groups. We develop an automated fall detection system with wearable motion sensor units …
Accelerometer-based fall detection using machine learning: Training and testing on real-world falls
Falling is a significant health problem. Fall detection, to alert for medical attention, has been
gaining increasing attention. Still, most of the existing studies use falls simulated in a …
gaining increasing attention. Still, most of the existing studies use falls simulated in a …
Automatic fall monitoring: A review
N Pannurat, S Thiemjarus, E Nantajeewarawat - Sensors, 2014 - mdpi.com
Falls and fall-related injuries are major incidents, especially for elderly people, which often
mark the onset of major deterioration of health. More than one-third of home-dwelling people …
mark the onset of major deterioration of health. More than one-third of home-dwelling people …
A machine learning multi-class approach for fall detection systems based on wearable sensors with a study on sampling rates selection
N Zurbuchen, A Wilde, P Bruegger - Sensors, 2021 - mdpi.com
Falls are dangerous for the elderly, often causing serious injuries especially when the fallen
person stays on the ground for a long time without assistance. This paper extends our …
person stays on the ground for a long time without assistance. This paper extends our …
UP-fall detection dataset: A multimodal approach
Falls, especially in elderly persons, are an important health problem worldwide. Reliable fall
detection systems can mitigate negative consequences of falls. Among the important …
detection systems can mitigate negative consequences of falls. Among the important …
SisFall: A fall and movement dataset
Research on fall and movement detection with wearable devices has witnessed promising
growth. However, there are few publicly available datasets, all recorded with smartphones …
growth. However, there are few publicly available datasets, all recorded with smartphones …
A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a …
Falls are the leading cause of injury-related morbidity and mortality among older adults.
Over 90% of hip and wrist fractures and 60% of traumatic brain injuries in older adults are …
Over 90% of hip and wrist fractures and 60% of traumatic brain injuries in older adults are …
Latest research trends in fall detection and prevention using machine learning: A systematic review
Falls are unusual actions that cause a significant health risk among older people. The
growing percentage of people of old age requires urgent development of fall detection and …
growing percentage of people of old age requires urgent development of fall detection and …
Review of fall detection techniques: A data availability perspective
A fall is an abnormal activity that occurs rarely; however, missing to identify falls can have
serious health and safety implications on an individual. Due to the rarity of occurrence of …
serious health and safety implications on an individual. Due to the rarity of occurrence of …
FallAllD: An open dataset of human falls and activities of daily living for classical and deep learning applications
M Saleh, M Abbas, RB Le Jeannes - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
In the last two decades, a wide variety of wearable fall detection systems have been
proposed. Most of them were based on machine learning. While the reported results give the …
proposed. Most of them were based on machine learning. While the reported results give the …