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Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect

Mobile and wearable devices embedded with multiple sensors for health monitoring and disease diagnosis are growing fields with the potential to provide efficient means for remote health management. A sensor-based health monitoring system offers an essential mechanism for real-time diagnosis and mana...

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Main Authors: Anikwe, Chioma Virginia, Nweke, Henry Friday, Ikegwu, Anayo Chukwu, Egwuonwu, Chukwunonso Adolphus, Onu, Fergus Uchenna, Alo, Uzoma Rita, Teh, Ying Wah
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Published: Elsevier 2022
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RA Public aspects of medicine
Online Access:http://eprints.um.edu.my/42113/
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spelling my.um.eprints.421132023-10-14T04:20:49Z http://eprints.um.edu.my/42113/ Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect Anikwe, Chioma Virginia Nweke, Henry Friday Ikegwu, Anayo Chukwu Egwuonwu, Chukwunonso Adolphus Onu, Fergus Uchenna Alo, Uzoma Rita Teh, Ying Wah RA Public aspects of medicine Mobile and wearable devices embedded with multiple sensors for health monitoring and disease diagnosis are growing fields with the potential to provide efficient means for remote health management. A sensor-based health monitoring system offers an essential mechanism for real-time diagnosis and management to detect/ predict, recommend treatment and prevent the onset of diseases. This paper aims to synthesize the research efforts on mobile and wearable sensors for health monitoring. It will investigate sensors, components of health monitoring systems, major application areas, challenges, and solutions faced during the implementation of health monitoring systems by researchers and practitioners. It was observed that sensors embedded in mobile and wearable devices for health monitoring are broadly categorized into homogeneous, dual, and heterogeneous sensors. In health monitoring, heterogeneous sensor-based is widely implemented and the most effective due to its ability to combine multiple sensors from various domains. The fusion of multiple sensors provides reliability, credibility, and better accuracy for monitoring multiple health parameters. We observed that researchers follow established procedures such as data collection, data transmission, preprocessing, feature extraction and development, data analysis, and evaluation of different algorithms for implementation of the health monitoring system. Supervised machine learning algorithms such as support vector machine, decision tree, k-nearest neighbors, and deep learning methods were the most implemented methods, while accuracy was the favored evaluation measure for health monitoring. Generally, we found that a health monitoring system is implemented to resolve health issues in the areas of human activity and posture monitoring, sleep disorder, sleep stage detection, fall monitoring in the elderly, depression, and mood swing detection. Other important areas include Parkinson's disease management, cardiac diseases monitoring, disease diagnosis, and well-being, and Corona virus detection and contact tracing to minimize infection rate. Furthermore, the review succinctly highlights various challenges impeding the development of sensor-based health monitoring systems with significant solutions that were recommended in the literature to ameliorate these challenges discussed. From the review, it can be acknowledged that various research efforts have been conducted to develop effective health monitoring systems, and many new systems have been implemented. However, there is still much work to be done which we have also discussed under future prospects. Elsevier 2022-09 Article PeerReviewed Anikwe, Chioma Virginia and Nweke, Henry Friday and Ikegwu, Anayo Chukwu and Egwuonwu, Chukwunonso Adolphus and Onu, Fergus Uchenna and Alo, Uzoma Rita and Teh, Ying Wah (2022) Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect. Expert Systems with Applications, 202. ISSN 0957-4174, DOI https://doi.org/10.1016/j.eswa.2022.117362 <https://doi.org/10.1016/j.eswa.2022.117362>. 10.1016/j.eswa.2022.117362
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic RA Public aspects of medicine
spellingShingle RA Public aspects of medicine
Anikwe, Chioma Virginia
Nweke, Henry Friday
Ikegwu, Anayo Chukwu
Egwuonwu, Chukwunonso Adolphus
Onu, Fergus Uchenna
Alo, Uzoma Rita
Teh, Ying Wah
Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect
description Mobile and wearable devices embedded with multiple sensors for health monitoring and disease diagnosis are growing fields with the potential to provide efficient means for remote health management. A sensor-based health monitoring system offers an essential mechanism for real-time diagnosis and management to detect/ predict, recommend treatment and prevent the onset of diseases. This paper aims to synthesize the research efforts on mobile and wearable sensors for health monitoring. It will investigate sensors, components of health monitoring systems, major application areas, challenges, and solutions faced during the implementation of health monitoring systems by researchers and practitioners. It was observed that sensors embedded in mobile and wearable devices for health monitoring are broadly categorized into homogeneous, dual, and heterogeneous sensors. In health monitoring, heterogeneous sensor-based is widely implemented and the most effective due to its ability to combine multiple sensors from various domains. The fusion of multiple sensors provides reliability, credibility, and better accuracy for monitoring multiple health parameters. We observed that researchers follow established procedures such as data collection, data transmission, preprocessing, feature extraction and development, data analysis, and evaluation of different algorithms for implementation of the health monitoring system. Supervised machine learning algorithms such as support vector machine, decision tree, k-nearest neighbors, and deep learning methods were the most implemented methods, while accuracy was the favored evaluation measure for health monitoring. Generally, we found that a health monitoring system is implemented to resolve health issues in the areas of human activity and posture monitoring, sleep disorder, sleep stage detection, fall monitoring in the elderly, depression, and mood swing detection. Other important areas include Parkinson's disease management, cardiac diseases monitoring, disease diagnosis, and well-being, and Corona virus detection and contact tracing to minimize infection rate. Furthermore, the review succinctly highlights various challenges impeding the development of sensor-based health monitoring systems with significant solutions that were recommended in the literature to ameliorate these challenges discussed. From the review, it can be acknowledged that various research efforts have been conducted to develop effective health monitoring systems, and many new systems have been implemented. However, there is still much work to be done which we have also discussed under future prospects.
format Article
author Anikwe, Chioma Virginia
Nweke, Henry Friday
Ikegwu, Anayo Chukwu
Egwuonwu, Chukwunonso Adolphus
Onu, Fergus Uchenna
Alo, Uzoma Rita
Teh, Ying Wah
author_facet Anikwe, Chioma Virginia
Nweke, Henry Friday
Ikegwu, Anayo Chukwu
Egwuonwu, Chukwunonso Adolphus
Onu, Fergus Uchenna
Alo, Uzoma Rita
Teh, Ying Wah
author_sort Anikwe, Chioma Virginia
title Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect
title_short Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect
title_full Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect
title_fullStr Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect
title_full_unstemmed Mobile and wearable sensors for data-driven health monitoring system: State-of-the-art and future prospect
title_sort mobile and wearable sensors for data-driven health monitoring system: state-of-the-art and future prospect
publisher Elsevier
publishDate 2022
url http://eprints.um.edu.my/42113/
_version_ 1781704597027422208
score 13.211869

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