Open AccessFall detecting clothes in realtime based seniors full body motion capture system using multiple inertial sensors
Author(s) -
Tri Raharjo Yudantoro,
F Pramuditya,
Roni Apriantoro,
S Jum’atun
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1108/1/012034
Subject(s) - motion capture , inertial measurement unit , computer science , waterfall model , simulation , artificial intelligence , motion (physics) , feature (linguistics) , process (computing) , computer vision , real time computing , software , linguistics , philosophy , programming language , operating system
The physical ability of the elderly will decrease along with the aging process, thus increasing the potential for falls. An elderly person who has experienced a fall and is not detected for a long time will bring many possible consequences. Early detection of an elderly fall will help to minimize this possibility by reducing the time between the occurrence of an event and the arrival of medical assistance The purpose of this research is to build a Fall Detecting Clothes in Realtime Based Art Full Body Motion Capture System Using Multiple Inertial Sensors. This system builds by Waterfall methodology where every research step is done in sequence, start from analysis, design, coding, testing. Testing methodology is black box, which is a test every feature function. The Fall Detecting Clothes in Real Time Based Systems Full Body Motion Capture System Using Multiple Inertial Sensors has been tested using black testing box with the results of all feature functions working properly. The system has been tested with several conditions with the results of all controls and output data works properly as well.