An internet of things based bed-egress alerting paradigm using wearable sensors in elderly care environment

Muhammad Awais, Mohsin Raza, Kamran Ali, Zulfiqar Ali, Muhammad Irfan, Omer Chughtai, Imran Khan, Sunghwan Kim*, Masood Ur Rehman

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Citations (Scopus)
5 Downloads (Pure)

Abstract

The lack of healthcare staff and increasing proportions of elderly population is alarming. The traditional means to look after elderly has resulted in 255,000 reported falls (only within UK). This not only resulted in extensive aftercare needs and surgeries (summing up to £4.4 billion) but also in added suffering and increased mortality. In such circumstances, the technology can greatly assist by offering automated solutions for the problem at hand. The proposed work offers an Internet of things (IoT) based patient bed-exit monitoring system in clinical settings, capable of generating a timely response to alert the healthcare workers and elderly by analyzing the wireless data streams, acquired through wearable sensors. This work analyzes two different datasets obtained from divergent families of sensing technologies, i.e., smartphone-based accelerometer and radio frequency identification (RFID) based accelerometer. The findings of the proposed system show good efficacy in monitoring the bed-exit and discriminate other ambulating activities. Furthermore, the proposed work manages to keep the average end-to-end system delay (i.e., communications of sensed data to Data Sink (DS)/Control Center (CC) + machine-based feature extraction and class identification + feedback communications to a relevant healthcare worker/elderly) below (Formula Persented) th of a second.

Original languageEnglish
Article number2498
JournalSensors (Switzerland)
Volume19
Issue number11
Early online date31 May 2019
DOIs
Publication statusPublished - 1 Jun 2019

Keywords

  • Accelerometer
  • Ambulating activities
  • Elderly population
  • Falls
  • Internet of things (IoT)
  • Patient monitoring
  • Radio-frequency identification (RFID)

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