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An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment
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 a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603575/ https://www.ncbi.nlm.nih.gov/pubmed/31159252 http://dx.doi.org/10.3390/s19112498 |
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author | Awais, Muhammad Raza, Mohsin Ali, Kamran Ali, Zulfiqar Irfan, Muhammad Chughtai, Omer Khan, Imran Kim, Sunghwan Ur Rehman, Masood |
author_facet | Awais, Muhammad Raza, Mohsin Ali, Kamran Ali, Zulfiqar Irfan, Muhammad Chughtai, Omer Khan, Imran Kim, Sunghwan Ur Rehman, Masood |
author_sort | Awais, Muhammad |
collection | PubMed |
description | 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: see text] of a second. |
format | Online Article Text |
id | pubmed-6603575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66035752019-07-17 An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment Awais, Muhammad Raza, Mohsin Ali, Kamran Ali, Zulfiqar Irfan, Muhammad Chughtai, Omer Khan, Imran Kim, Sunghwan Ur Rehman, Masood Sensors (Basel) Article 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: see text] of a second. MDPI 2019-05-31 /pmc/articles/PMC6603575/ /pubmed/31159252 http://dx.doi.org/10.3390/s19112498 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Awais, Muhammad Raza, Mohsin Ali, Kamran Ali, Zulfiqar Irfan, Muhammad Chughtai, Omer Khan, Imran Kim, Sunghwan Ur Rehman, Masood An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment |
title | An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment |
title_full | An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment |
title_fullStr | An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment |
title_full_unstemmed | An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment |
title_short | An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment |
title_sort | internet of things based bed-egress alerting paradigm using wearable sensors in elderly care environment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603575/ https://www.ncbi.nlm.nih.gov/pubmed/31159252 http://dx.doi.org/10.3390/s19112498 |
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