JOURNAL ARTICLE

Remote health monitoring of elderly through wearable sensors

Mohammed Al-KhafajiyThar BakerCarl ChalmersMuhammad AsimHoshang KolivandMuhammad FahimAtif Waraich

Year: 2019 Journal:   Multimedia Tools and Applications Vol: 78 (17)Pages: 24681-24706   Publisher: Springer Science+Business Media

Abstract

Due to a rapidly increasing aging population and its associated challenges in health and social care, Ambient Assistive Living has become the focal point for both researchers and industry alike. The need to manage or even reduce healthcare costs while improving the quality of service is high government agendas. Although, technology has a major role to play in achieving these aspirations, any solution must be designed, implemented and validated using appropriate domain knowledge. In order to overcome these challenges, the remote real-time monitoring of a person’s health can be used to identify relapses in conditions, therefore, enabling early intervention. Thus, the development of a smart healthcare monitoring system, which is capable of observing elderly people remotely, is the focus of the research presented in this paper. The technology outlined in this paper focuses on the ability to track a person’s physiological data to detect specific disorders which can aid in Early Intervention Practices. This is achieved by accurately processing and analysing the acquired sensory data while transmitting the detection of a disorder to an appropriate career. The finding reveals that the proposed system can improve clinical decision supports while facilitating Early Intervention Practices. Our extensive simulation results indicate a superior performance of the proposed system: low latency (96% of the packets are received with less than 1 millisecond) and low packets-lost (only 2.2% of total packets are dropped). Thus, the system runs efficiently and is cost-effective in terms of data acquisition and manipulation.

Keywords:
Computer science Wearable computer Health care Network packet Intervention (counseling) Wearable technology Risk analysis (engineering) Computer security Real-time computing Human–computer interaction Embedded system Medicine Nursing

Metrics

347
Cited By
20.84
FWCI (Field Weighted Citation Impact)
51
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Non-Invasive Vital Sign Monitoring
Physical Sciences →  Engineering →  Biomedical Engineering

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