IoT-based continuous glucose monitoring system: A feasibility study

Gia, Tuan Nguyen; Ali, Mai; Dhaou, Imed Ben; Rahmani, Amir M.; Westerlund, Tomi; Liljeberg, Pasi; Tenhunen, Hannu

doi:10.1016/j.procs.2017.05.359

Cited by 107 publications

(44 citation statements)

References 12 publications

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“…Optical images before and after assembling with the CP electrode are shown in Figure 11F,G. Other diseases such as diabetes are also targeted in eHealth diagnosis because of their relevance worldwide [103][104][105][106]. In this paper we present many approaches based on microfluidics, and we summarize their most relevant features in terms of analytes, detection method, and limits of detection in Table 1.…”

Section: A B Cmentioning

confidence: 99%

Microfluidic Point-of-Care Devices: New Trends and Future Prospects for eHealth Diagnostics

Mejía‐Salazar

Cruz

Vásques

et al. 2020

Sensors

145

111

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Point-of-care (PoC) diagnostics is promising for early detection of a number of diseases, including cancer, diabetes, and cardiovascular diseases, in addition to serving for monitoring health conditions. To be efficient and cost-effective, portable PoC devices are made with microfluidic technologies, with which laboratory analysis can be made with small-volume samples. Recent years have witnessed considerable progress in this area with “epidermal electronics”, including miniaturized wearable diagnosis devices. These wearable devices allow for continuous real-time transmission of biological data to the Internet for further processing and transformation into clinical knowledge. Other approaches include bluetooth and WiFi technology for data transmission from portable (non-wearable) diagnosis devices to cellphones or computers, and then to the Internet for communication with centralized healthcare structures. There are, however, considerable challenges to be faced before PoC devices become routine in the clinical practice. For instance, the implementation of this technology requires integration of detection components with other fluid regulatory elements at the microscale, where fluid-flow properties become increasingly controlled by viscous forces rather than inertial forces. Another challenge is to develop new materials for environmentally friendly, cheap, and portable microfluidic devices. In this review paper, we first revisit the progress made in the last few years and discuss trends and strategies for the fabrication of microfluidic devices. Then, we discuss the challenges in lab-on-a-chip biosensing devices, including colorimetric sensors coupled to smartphones, plasmonic sensors, and electronic tongues. The latter ones use statistical and big data analysis for proper classification. The increasing use of big data and artificial intelligence methods is then commented upon in the context of wearable and handled biosensing platforms for the Internet of things and futuristic healthcare systems.

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Section: A B Cmentioning

confidence: 99%

Microfluidic Point-of-Care Devices: New Trends and Future Prospects for eHealth Diagnostics

Mejía‐Salazar

Cruz

Vásques

et al. 2020

Sensors

145

111

View full text Add to dashboard Cite

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“…They make use of standardized technologies to monitor glucose levels, as well as body temperature. With this kind of architecture, it is possible to have readings in real time and to store the information in back-end type servers [21]. A patient's caregivers can track his or her evolution from their mobile device or by accessing a web page.…”

Section: Related Workmentioning

confidence: 99%

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

et al. 2020

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Diabetes mellitus (DM) is a metabolic disorder characterized by blood glucose levels above normal limits. The impact of this disease on the population has increased in recent years. It is already a public health problem worldwide and one of the leading causes of death. Recently, several proposals have been developed for better and regular monitoring of glucose. However, theses proposals do not discard erroneous readings and they are not able to anticipate a critical condition. In this work, we propose an algorithm based on the double moving average supported by an IoT architecture to prevent possible complications in elderly patients. The algorithm uses historical readings to construct a series. Given a number of periods, it is possible to calculate averages of different subsets and trends for the next periods and, in this way, the prognosis is obtained. With the prognosis, it is possible to notify the doctor and relatives in advance about a possible critical condition in the patient. The aim of our work is to validate the architecture and prognosis algorithm used for elderly persons. Tests of the algorithm and the architecture were performed with different readings and it was shown that the system generated corresponding notifications before the glucose values were higher than those defined by the WHO (World Health Organization), thus avoiding unnecessary alarms.

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“…However, modern IoT-based continuous monitoring systems for sugar levels are not numerous and existing systems also have some restrictions. In [19], using IoT, the architecture for glucose level monitoring system is developed. The system provides actual information about the amount of glucose in blood, including body temperature and contextual data (e.g.…”

Section: Intelligent Iot Applicationsmentioning

confidence: 99%

Opportunities of the Internet of Things in the Monitoring of the Physiological State and Location of Personnel on Offshore Oil Platform

Mammadova¹,

Jabrayilova²

2018

JPIT

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The article explores the opportunities of using the Internet of Things to ensure the safety of personnel on offshore oil platform. To this end, the IoT applications and technologies are analyzed for the monitoring of the physiological state and location of personnel. The article presents the opportunities of using IoT with cloud technologies, Big Data technologies, and artificial intelligence for system development which enables to monitor and, if necessary, to make appropriate decisions based on the systematic monitoring of the state of personnel.

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IoT-based continuous glucose monitoring system: A feasibility study

Cited by 107 publications

References 12 publications

Microfluidic Point-of-Care Devices: New Trends and Future Prospects for eHealth Diagnostics

Microfluidic Point-of-Care Devices: New Trends and Future Prospects for eHealth Diagnostics

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

Opportunities of the Internet of Things in the Monitoring of the Physiological State and Location of Personnel on Offshore Oil Platform

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