In this paper, the recognition of and the differentiation between fall activities and activities of
daily living (ADL) was performed using the MobiFall dataset. A large database was …

The high rate of falls incidence among the elderly calls for the development of reliable and
robust fall detection systems. A number of such systems have been proposed, with claims of …

Fall detection receives significant attention in the field of preventive medicine, wellness
provision and assisted living, especially for the elderly. As a result, numerous commercial …

We propose a novel computer vision based fall detection system using deep learning
methods to analyse the postures in a smart home environment for detecting fall activities …

Nowadays, recognizing human activities is an important subject; it is exploited widely and
applied to many fields in real-life, especially health care or context aware application …

Wearable sensors are becoming popular for remote health monitoring as technology
improves and cost reduces. One area in which wearable sensors are increasingly being …

Falls are the primary cause of accidents for the elderly in living environment. Falls frequently
cause fatal and non-fatal injuries that are associated with a large amount of medical costs …

The danger of falling among the elderly is a public concern and is becoming an important
issue that needs further attention. Sensors embedded in smartphones provide information …

Falls among older people remain a very important public healthcare issue. Every year over
11 million falls are registered in the US alone. This paper presents a practical real time fall …

As we grow old, our desire for being independence does not decrease while our health
needs to be monitored more frequently. Accidents such as falling can be a serious problem …