Cited by 146Context-Aware Activity Recognition SystemsWireless Body Area NetworksEnergy Efficient Wireless Sensor Networks

Energy efficient wearable sensor node for IoT-based fall detection systems

Open access
Nguyen Gia, Tuan, Sarker, Victor Kathan, Tcarenko, Igor, Rahmani, Amir M., Westerlund, Tomi, Liljeberg, Pasi, Tenhunen, Hannu·2018·Microprocessors and Microsystems

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Registry

Crossref · 10.1016/j.micpro.2017.10.014

Cites

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  • Wearable sensors have been highly successful in fall detection.

    “Wearable sensors have been highly successful in fall detection [50,106,107].”

    From Wearables and the Medical Revolution (2018) · cites this paper as [106]

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Cites

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Research works printed but not linked: 1

  1. C. Shuo, "Fall detection system using arduino fio," in Proceedings of the IRC Conference on Science, Engineering and Technology, Singapore, vol. 13, 2015.

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Authors
Nguyen Gia, T., Sarker, V. K., Tcarenko, I., Rahmani, A. M., Westerlund, T., Liljeberg, P., & Tenhunen, H.
Affiliations
  • University of Turku (FI)
  • TU Wien (AT)
Venue
Microprocessors and Microsystems
Publisher
Elsevier BV
Published
2018-02
Volume
56
Pages
34-46
ISSN
0141-9331 (ISSN-L)
OpenAlex
W2767165810
Cited by
146
References
47
Citations by year
2026: 6 · 2025: 12 · 2024: 9 · 2023: 13 · 2022: 18 · 2021: 17 · 2020: 35 · 2019: 25 · 2018: 11
FWCI
8.06
Type
journal article
Language
en
Open access
Locations
  • Microprocessors and Microsystems (publishedVersion)
  • UTUPub (University of Turku) (submittedVersion)
Funders
  • University of Turku Graduate School
  • Academy of Finland
  • Nokia Foundation
  • TES
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
  • Physical Sciences › Computer Science › Computer Networks and Communications › Energy Efficient Wireless Sensor Networks
Keywords
wearable sensor nodes, fall detection, energy efficiency, Internet of Things, elderly monitoring, flexible wearable devices, energy consumption analysis, sampling frequency, transmission protocols, transmission rate, battery life

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