Related papers: CareFall: Automatic Fall Detection through Wearabl…
Fall is one of the major health threats and obstacles to independent living for elders, timely and reliable fall detection is crucial for mitigating the effects of falls. In this paper, leveraging the fine-grained Channel State Information…
As the percentage of elderly people in developed countries increases worldwide, the healthcare of this collective is a worrying matter, especially if it includes the preservation of their autonomy. In this direction, many studies are being…
Falls are a major cause of injury and mortality among older adults, yet most incidents occur in private indoor environments where monitoring must balance effectiveness with privacy. Existing privacy-preserving fall detection approaches,…
Falls represent one of the most detrimental occurrences for the elderly. Given the continually increasing ageing demographic, there is a pressing demand for advancing fall detection systems. The swift progress in sensor networks and the…
Nowadays, detecting aberrant health issues is a difficult process. Falling, especially among the elderly, is a severe concern worldwide. Falls can result in deadly consequences, including unconsciousness, internal bleeding, and often times,…
Falling, especially in the elderly, is a critical issue to care for and surveil. There have been many studies focusing on fall detection. However, from our survey, there is still no research indicating the prior-fall activities, which we…
This paper presents an innovative approach to address the pressing concern of fall incidents among the elderly by developing an accurate fall detection system. Our proposed system combines state-of-the-art technologies, including…
Falls among elderly residents in assisted living homes pose significant health risks, often leading to injuries and a decreased quality of life. Current fall detection solutions typically rely on sensor-based systems that require dedicated…
Fall prevalence is high among elderly people, which is challenging due to the severe consequences of falling. This is why rapid assistance is a critical task. Ambient assisted living (AAL) uses recent technologies such as 5G networks and…
A fall is an abnormal activity that occurs rarely, so it is hard to collect real data for falls. It is, therefore, difficult to use supervised learning methods to automatically detect falls. Another challenge in using machine learning…
Devices and sensors for identification of fallers can be used to implement actions to prevent falls and to allow the elderly to live an independent life while reducing the long-term care costs. In this study we aimed to investigate the…
Accurate fall detection for the assistance of older people is crucial to reduce incidents of deaths or injuries due to falls. Meanwhile, a vision-based fall detection system has shown some significant results to detect falls. Still,…
In recent years a growing interest on action recognition is observed, including detection of fall accident for the elderly. However, despite many efforts undertaken, the existing technology is not widely used by elderly, mainly because of…
This paper presents a collaborative fall detection and response system integrating Wi-Fi sensing with robotic assistance. The proposed system leverages channel state information (CSI) disruptions caused by movements to detect falls in…
Background/Objectives: Falls represent a major health concern for stroke survivors, necessitating effective risk assessment tools. This study proposes the Instrumented Fall Risk Assessment (IFRA) scale, a novel screening tool derived from…
Military personnel and security agents often face significant physical risks during conflict and engagement situations, particularly in urban operations. Ensuring the rapid and accurate communication of incidents involving injuries is…
This paper proposes a real-time embedded fall detection system using a DVS(Dynamic Vision Sensor) that has never been used for traditional fall detection, a dataset for fall detection using that, and a DVS-TN(DVS-Temporal Network). The…
Deep learning based fall detection is one of the crucial tasks for intelligent video surveillance systems, which aims to detect unintentional falls of humans and alarm dangerous situations. In this work, we propose a simple and efficient…
Existing deep learning approaches for wearable fall detection systems rely on self-attention mechanisms that impose quadratic computational overhead, distributing weights across all time steps. This global weight distribution impairs the…
This study investigates fall risk prediction in older adults using various machine learning models trained on accelerometric, non-accelerometric, and combined data from 146 participants. Models combining both data types achieved superior…