A wearable device for fall detection elderly people using tri dimensional accelerometer

2016 ◽  
Author(s):  
A. Kurniawan ◽  
A. R. Hermawan ◽  
I. K. E. Purnama
Keyword(s):  
Elderly People ◽  
Fall Detection ◽  
Wearable Device

scholarly journals Mobile activity recognition and fall detection system for elderly people using Ameva algorithm

2017 ◽  
Vol 34 ◽  
pp. 3-13 ◽  
Author(s):  
Miguel Ángel Álvarez de la Concepción ◽  
Luis Miguel Soria Morillo ◽  
Juan Antonio Álvarez García ◽  
Luis González-Abril
Keyword(s):  
Elderly People ◽  
Activity Recognition ◽  
Detection System ◽  
Fall Detection

scholarly journals Automatic Fall Detection System of Unsupervised Elderly People Using Smartphone

2017 ◽  
Author(s):  
Zishan Zahidul Islam ◽  
Syed Mahir Tazwar ◽  
Md. Zahidul Islam ◽  
Seiichi Serikawa ◽  
Md. Atiqur Rahman Ahad
Keyword(s):  
Elderly People ◽  
Detection System ◽  
Fall Detection

scholarly journals Fall Detection for Elderly People Using the Variation of Key Points of Human Skeleton

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 154786-154795 ◽  
Author(s):  
Abdessamad Youssfi Alaoui ◽  
Sanaa El Fkihi ◽  
Rachid Oulad Haj Thami
Keyword(s):  
Elderly People ◽  
Fall Detection ◽  
Human Skeleton ◽  
Key Points

scholarly journals Vision-based fall detection system for improving safety of elderly people

2017 ◽  
Vol 20 (6) ◽  
pp. 49-55 ◽  
Author(s):  
Fouzi Harrou ◽  
Nabil Zerrouki ◽  
Ying Sun ◽  
Amrane Houacine
Keyword(s):  
Elderly People ◽  
Detection System ◽  
Fall Detection

Design and Realization of an Early Pre-Impact Fall Alarm System Based on MEMS Inertial Sensing Units

2013 ◽  
Vol 461 ◽  
pp. 659-666
Author(s):  
Hui Qi Li ◽  
Ding Liang ◽  
Yun Kun Ning ◽  
Qi Zhang ◽  
Guo Ru Zhao
Keyword(s):  
Elderly People ◽  
Unintentional Injury ◽  
Fall Detection ◽  
The Elderly ◽  
Detection Algorithm ◽  
Detection Sensitivity ◽  
Alarm System ◽  
Inertial Sensing ◽  
Security Problem ◽  
Fall Protection

Falls are the second leading cause of unintentional injury deaths worldwide, so how to prevent falls has become a safety and security problem for elderly people. At present, because the sensing modules of most fall alarm devices generally only integrate the single 3-axis accelerometer, so the measured accuracy of sensing signals is limited. It results in that these devices can only achieve the alarm of post-fall detection but not the early pre-impact fall recognition in real fall applications. Therefore, this paper aimed to develop an early pre-impact fall alarm system based on high-precision inertial sensing units. A multi-modality sensing module embedded fall detection algorithm was developed for early pre-impact fall detection. The module included a 3-axis accelerometer, a 3-axis gyroscope and a 3-axis magnetometer, which could arouse the information of early pre-impact fall warning by a buzzer and a vibrator. Total 81 times fall experiments from 9 healthy subjects were conducted in simulated fall conditions. By combination of the early warning threshold algorithm, the result shows that the detection sensitivity can achieve 98.61% with a specificity of 98.61%, and the average pre-impact lead time is 300ms. In the future, GPS, GSM electronic modules and wearable protected airbag will be embedded in the system, which will enhance the real-time fall protection and timely immediate aid immensely for the elderly people.

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