eprintid: 3048
rev_number: 11
eprint_status: archive
userid: 12
dir: disk0/00/00/30/48
datestamp: 2018-08-28 08:35:14
lastmod: 2018-08-28 08:35:14
status_changed: 2018-08-28 08:35:14
type: article
metadata_visibility: show
creators_name: Pham, Van Thanh
creators_name: Tran, Duc Tan
creators_name: Nguyen, Dinh Chinh
creators_name: Nguyen, Duc Anh
creators_name: Dang, Nhu Dinh
creators_name: El-Sayed Mahmoud, El-Rabaie
creators_name: Sandrasegaran, Kumbesan
creators_id: phamvanthanh1209@gmail.com
creators_id: tantd@vnu.edu.vn
creators_id: chinhnd@vnu.edu.vn
creators_id: anhnd@gmail.com
creators_id: dangnhu@gmail.com
creators_id: srabie1@yahoo.com
creators_id: kumbesan.sandrasegaran@uts.edu.au
title: Development of a Real-Time, Simple and High-Accuracy Fall Detection System for Elderly Using 3-DOF Accelerometers
ispublished: pub
subjects: ElectronicsandComputerEngineering
subjects: Scopus
subjects: isi
divisions: fac_fet
abstract: Falls represent a major problem for the elderly people aged 60 or above. There are many monitoring systems which are currently available to detect the fall. However, there is a great need to propose a system which is of optimal effectiveness. In this paper, we propose to develop a low-cost fall detection system to precisely detect an event when an elderly person accidentally falls. The fall detection algorithm compares the acceleration with lower fall threshold and upper fall threshold values to accurately detect a fall event. The post-fall recognition module is the combination of posture recognition and vertical velocity estimation that has been added to our proposed method to enhance the performance and accuracy. In case of a fall, our device will transmit the location information to the contacts instantly via SMS and voice call. A smartphone application will ensure that the notifications are delivered to the elderly person's relatives so that medical attention can be provided with minimal delay. The system was tested by volunteers and achieved 100% sensitivity and accuracy. This was confirmed by testing with public datasets and it also achieved the same percentage in sensitivity and accuracy as in our recorded datasets.
date: 2018-08-15
date_type: published
publisher: Springer
official_url: https://doi.org/10.1007/s13369-018-3496-4
id_number: https://doi.org/10.1007/s13369-018-3496-4
full_text_status: public
publication: Arabian Journal for Science and Engineering
pagerange: 1-14
refereed: TRUE
issn: 2191-4281
related_url_url: https://link.springer.com/article/10.1007/s13369-018-3496-4
citation:   Pham, Van Thanh and Tran, Duc Tan and Nguyen, Dinh Chinh and Nguyen, Duc Anh and Dang, Nhu Dinh and El-Sayed Mahmoud, El-Rabaie and Sandrasegaran, Kumbesan  (2018) Development of a Real-Time, Simple and High-Accuracy Fall Detection System for Elderly Using 3-DOF Accelerometers.  Arabian Journal for Science and Engineering .   pp. 1-14.  ISSN 2191-4281     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3048/1/10.1007_s13369-018-3496-4.pdf