Product Design for Senior Population: A Wearable System for Physical Protection and Fall Detection

2021 ◽  
pp. 373-386
Author(s):  
Miguel Terroso ◽  
Ricardo Simoes
Author(s):  
Paul C.-P. Chao ◽  
Li-Chi Hsu ◽  
Yu-Feng Li ◽  
Chin-Wei Chun

A novel wireless circuit module is designed in this study to perform ubiquitous fall detections and then real-time fall detections of help messages. It is a common trend that as the demand for living quality increases tremendously while the technologies of electronics and medicine advances greatly, personal cares are elevated to the next level. As for the aging society, the issue of injuries due to falls among senior population arises rapidly [1,2]. Costly prices are often paid as the elderly falls without notice from companions at the site. Therefore, various modules and/or systems of automatic and wireless fall detection are developed into a past pace. Such fall-detection modules are demanded to be able to automatically detect falls of subjects and then send the help message to a remote hospital for an immediate help.


2021 ◽  
Vol 7 (3) ◽  
pp. 42
Author(s):  
Abderrazak Iazzi ◽  
Mohammed Rziza ◽  
Rachid Oulad Haj Thami

The majority of the senior population lives alone at home. Falls can cause serious injuries, such as fractures or head injuries. These injuries can be an obstacle for a person to move around and normally practice his daily activities. Some of these injuries can lead to a risk of death if not handled urgently. In this paper, we propose a fall detection system for elderly people based on their postures. The postures are recognized from the human silhouette which is an advantage to preserve the privacy of the elderly. The effectiveness of our approach is demonstrated on two well-known datasets for human posture classification and three public datasets for fall detection, using a Support-Vector Machine (SVM) classifier. The experimental results show that our method can not only achieves a high fall detection rate but also a low false detection.


2008 ◽  
Vol 41 (16) ◽  
pp. 3475-3481 ◽  
Author(s):  
M.N. Nyan ◽  
Francis E.H. Tay ◽  
E. Murugasu

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