Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in this directi...
UNLABELLED: Community mobility, encompassing both active (e.g., walking) and passive (e.g., driving) transport, plays a crucial role in maintaining autonomy and social interaction among older adults. This study aimed to quantify community mobility in...
As many countries face rapid population aging, the supply of manpower for caregiving falls far short of the increasing demand for care. Therefore, if the care system can continuously recognize and track the care recipient and, at the first sign of a ...
Due to the limitations that falls have on humans, early detection of these becomes essential to avoid further damage. In many applications, various technologies are used to acquire accurate information from individuals such as wearable sensors, envir...
Journal of the American Medical Directors Association
39701553
OBJECTIVES: The study aimed to develop a machine learning (ML) model to predict early postdischarge falls in older adults using data that are easy to collect in acute care hospitals. This may reduce the burden imposed by complex measures on patients ...
Millions of people around the globe are impacted by falls annually, making it a significant public health concern. Falls are particularly challenging to detect in real time, as they often occur suddenly and with little warning, highlighting the need ...
Fall from a height trauma is characterized by a multiplicity of injuries, related to multiple factors. The height of the fall is the factor that most influences the kinetic energy of the body and appears to be one of the factors that most affects the...
BACKGROUND: Multiple sclerosis (MS) is an autoimmune disease that can increase the risk of falls in patients due to various factors. Traditional clinical assessments may not effectively identify those at risk of falling.
Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction model to predict the fall risk category among community-dwelling older adults, leading to earlier i...