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Internet of things based fall detection and heart rate monitoring system for senior citizens

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 3 (2022)

DOI
10.11591/ijece.v12i3.pp3204-3216
ISSN
2722-2578, 2088-8708
Published
2022-06-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Falls cause the maximum number of injuries, deaths, and hospitalizations due to injury for senior citizens worldwide. So, fall detection is essential in the health care of senior citizens. Present methods lack either accuracy or comfortability. The design of fall detection and heart rate monitoring system for senior citizens has been presented in this paper. The hardware interface includes wearable monitoring devices based on a tri-axial accelerometer and Bluetooth module that makes a wireless connection by software interface (mobile application) to the caregiver. Global positioning system (GPS) can also track the location of the elder. For detecting falls accurately, an effective fall detection algorithm is developed and used. The performance parameters of the fall detection system are accuracy (97.6%), sensitivity (92.8%), and specificity (100%). A pulse sensor is used for monitoring the heart rate of the elder. The device is put on the hips to increase comfortability. Whenever the elder's fall is detected, the device can send information on fall data and heart rate with location to the respective caregiver successfully. So, this device can minimize the injury and health cost of a fallen person as a victim can get help within a short time.

Collaboration network of the authors

16 authors · 35 co-authorship links · 7 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Chittagong University of Engineering & Technology
  • Bangladesh University of Engineering and Technology
  • City University of Hong Kong
  • Khulna University of Engineering and Technology
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Md. Azad HossainChittagong University of Engineering & Technology2
Nur MohammadChittagong University of Engineering & Technology1
Md. Asiful IslamBangladesh University of Engineering and Technology1
Tarequl KarimChittagong University of Engineering & Technology1
Mehdi Hasan ChowdhuryChittagong University of Engineering & Technology1
Ray C. C. CheungCity University of Hong Kong1
Muhammad Asad RahmanChittagong University of Engineering & Technology1
Mohiuddin AhmadKhulna University of Engineering and Technology1
Rubana Hoque ChowdhuryAffiliation unknown1
Roma SultanaAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Internet of things based fall detection and heart rate monitoring system for senior citizens</dc:title><dc:creator>Sarowar, Md. Hasib</dc:creator><dc:creator>Khondakar, Md. Fazlul karim</dc:creator><dc:creator>Roy, Himaddri Shakhar</dc:creator><dc:creator>Ullah, Habib</dc:creator><dc:creator>Ahmed, Riaj</dc:creator><dc:creator>Hossain, Quazi Delwar</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span&amp;gt;Falls cause the maximum number of injuries, deaths, and hospitalizations due to injury for senior citizens worldwide. So, fall detection is essential in the health care of senior citizens. Present methods lack either accuracy or comfortability. The design of fall detection and heart rate monitoring system for senior citizens has been presented in this paper. The hardware interface includes wearable monitoring devices based on a tri-axial accelerometer and Bluetooth module that makes a wireless connection by software interface (mobile application) to the caregiver. Global positioning system (GPS) can also track the location of the elder. For detecting falls accurately, an effective fall detection algorithm is developed and used. The performance parameters of the fall detection system are accuracy (97.6%), sensitivity (92.8%), and specificity (100%). A pulse sensor is used for monitoring the heart rate of the elder. The device is put on the hips to increase comfortability. Whenever the elder's fall is detected, the device can send information on fall data and heart rate with location to the respective caregiver successfully. So, this device can minimize the injury and health cost of a fallen person as a victim can get help within a short time.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2022-06-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v12i3.pp3204-3216</dc:identifier><dc:identifier>10.11591/ijece.v12i3.pp3204-3216</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 12 No 3 (2022); 3204</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/24317/15710</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>