Fall-MobileGuard: a Smart Real-Time Fall Detection System

2015 ◽  
Author(s):  
Giancarlo Fortino ◽  
Raffaele Gravina
Keyword(s):  
Real Time ◽  
Detection System ◽  
Fall Detection ◽  
Time Fall

Radar Based Real-Time Fall Detection System with Low Power Consumption

2021 ◽  
Author(s):  
Jincheng Lu ◽  
Zixuan Ou ◽  
Ziyu Liu ◽  
Cheng Han ◽  
Wenbin Ye
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Real Time ◽  
Detection System ◽  
Fall Detection ◽  
Low Power Consumption ◽  
Time Fall

Implementation of a real-time fall detection system for elderly Korean farmers using an insole-integrated sensing device

2019 ◽  
Vol 48 (1) ◽  
pp. 22-42 ◽  
Author(s):  
Insoo Kim ◽  
Kyung-Suk Lee ◽  
Kyungran Kim ◽  
Kyungsu Kim ◽  
Hye-Seon Chae ◽  
...  
Keyword(s):  
Real Time ◽  
Detection System ◽  
Fall Detection ◽  
Time Fall

Towards a Real-Time Fall Detection System using Kinect Sensor

2016 ◽  
Vol 6 (1) ◽  
pp. 41-58 ◽  
Author(s):  
Nadia Baha ◽  
Eden Beloudah ◽  
Mehdi Ousmer
Keyword(s):  
Real Time ◽  
Detection System ◽  
Fall Detection ◽  
Microsoft Kinect ◽  
False Alarms ◽  
Depth Information ◽  
Detection Rates ◽  
Major Health Problem ◽  
Major Health ◽  
Time Fall

Falls are the major health problem among older people who live alone in their home. In the past few years, several studies have been proposed to solve the dilemma especially those which exploit video surveillance. In this paper, in order to allow older adult to safely continue living in home environments, the authors propose a method which combines two different configurations of the Microsoft Kinect: The first one is based on the person's depth information and his velocity (Ceiling mounted Kinect). The second one is based on the variation of bounding box parameters and its velocity (Frontal Kinect). Experimental results on real datasets are conducted and a comparative evaluation of the obtained results relative to the state-of-art methods is presented. The results show that the authors' method is able to accurately detect several types of falls in real-time as well as achieving a significant reduction in false alarms and improves detection rates.

A Real-time Fall Detection System Using a Depth Camera

2016 ◽  
Author(s):  
Nan Bao ◽  
Ling-Kai Gu ◽  
Yi-Feng Zheng ◽  
Xiao-Lei Wang
Keyword(s):  
Real Time ◽  
Detection System ◽  
Fall Detection ◽  
Depth Camera ◽  
Time Fall
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