Power- and delay-awareness of health telemonitoring services: the mobihealth system case study

Wac, Katarzyna; Bargh, Mortaza S.; Beijnum, B.-J. van; Bults, Richard; Pawar, Pravin; Peddemors, Arjan J. H.

doi:10.1109/jsac.2009.090514

Cited by 23 publications

(7 citation statements)

References 21 publications

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“…Despite the mentioned benefits and its multiple applications in diverse fields [23], there are not many practical examples of the use of fog computing in healthcare applications. A good compilation of fog computing based healthcare applications can be found in [24], which describes potential applications for monitoring Chronic Obstructive Pulmonary Disease (COPD) patients [25], tools for in-home Parkinson disease treatments [26] or hospital platforms that make use of e-textiles [27] and wireless sensor networks [28]. Similarly, other researchers proposed applications for healthcare monitoring in smart homes [29] or for diagnosing and preventing outbreaks of certain viruses [30].…”

Section: Related Workmentioning

confidence: 99%

Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care

Fernández‐Caramés

Froiz-Míguez

Blanco-Novoa

et al. 2019

Sensors

116

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Diabetes patients suffer from abnormal blood glucose levels, which can cause diverse health disorders that affect their kidneys, heart and vision. Due to these conditions, diabetes patients have traditionally checked blood glucose levels through Self-Monitoring of Blood Glucose (SMBG) techniques, like pricking their fingers multiple times per day. Such techniques involve a number of drawbacks that can be solved by using a device called Continuous Glucose Monitor (CGM), which can measure blood glucose levels continuously throughout the day without having to prick the patient when carrying out every measurement. This article details the design and implementation of a system that enhances commercial CGMs by adding Internet of Things (IoT) capabilities to them that allow for monitoring patients remotely and, thus, warning them about potentially dangerous situations. The proposed system makes use of smartphones to collect blood glucose values from CGMs and then sends them either to a remote cloud or to distributed fog computing nodes. Moreover, in order to exchange reliable, trustworthy and cybersecure data with medical scientists, doctors and caretakers, the system includes the deployment of a decentralized storage system that receives, processes and stores the collected data. Furthermore, in order to motivate users to add new data to the system, an incentive system based on a digital cryptocurrency named GlucoCoin was devised. Such a system makes use of a blockchain that is able to execute smart contracts in order to automate CGM sensor purchases or to reward the users that contribute to the system by providing their own data. Thanks to all the previously mentioned technologies, the proposed system enables patient data crowdsourcing and the development of novel mobile health (mHealth) applications for diagnosing, monitoring, studying and taking public health actions that can help to advance in the control of the disease and raise global awareness on the increasing prevalence of diabetes.

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Section: Related Workmentioning

confidence: 99%

Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care

Fernández‐Caramés

Froiz-Míguez

Blanco-Novoa

et al. 2019

Sensors

116

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“…A two-tier architecture is considered in [ 119 ] to implement a remote monitoring application for patients with Chronic Obstructive Pulmonary Disease (COPD). Bluetooth is used as the WBAN technology for the communication between the sensors and the coordinating node (e.g., a PDA).…”

Section: End-to-end Solutions For M2m Communicationmentioning

confidence: 99%

A Survey on M2M Systems for mHealth: A Wireless Communications Perspective

Kartsakli

Lalos

Antonopoulos

et al. 2014

Sensors

103

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In the new era of connectivity, marked by the explosive number of wireless electronic devices and the need for smart and pervasive applications, Machine-to-Machine (M2M) communications are an emerging technology that enables the seamless device interconnection without the need of human interaction. The use of M2M technology can bring to life a wide range of mHealth applications, with considerable benefits for both patients and healthcare providers. Many technological challenges have to be met, however, to ensure the widespread adoption of mHealth solutions in the future. In this context, we aim to provide a comprehensive survey on M2M systems for mHealth applications from a wireless communication perspective. An end-to-end holistic approach is adopted, focusing on different communication aspects of the M2M architecture. Hence, we first provide a systematic review of Wireless Body Area Networks (WBANs), which constitute the enabling technology at the patient's side, and then discuss end-to-end solutions that involve the design and implementation of practical mHealth applications. We close the survey by identifying challenges and open research issues, thus paving the way for future research opportunities.

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“…A two-tier architecture is considered in [32] In some works, ambient sensor networks for environmental monitoring are employed in conjunction with WBANs, in order to provide additional information on the patient's environment, such as temperature, humidity and light conditions. Along this line, a three-tier network architecture is proposed in [33], for the remote monitoring of elderly or chronic patients in their residence.…”

Section: B Testbed Implementation Of M2m Solutionsmentioning

confidence: 99%

Machine-to-machine (M2M) communications for e-health applications

Kartsakli

Lalos

Antonopoulos

et al. 2015

Machine-to-Machine (M2M) Communications

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The emerging technology of Machine-to-Machine (M2M) communications is bringing a paradigm shift in healthcare delivery. A broad range of e-Health applications can be conceived, with considerable benefits for both patients and healthcare providers. Many technological challenges have to be met, however, to ensure the widespread adoption of e-Health solutions in the future. In this context, we aim to provide a comprehensive overview on M2M systems for e-Health applications from a wireless communication perspective. We provide an overview of the candidate wireless technologies that are suitable for different parts of the M2M system architecture and then show how these technologies are seamlessly integrated to provide an end-to-end e-Health solution. In particular, we discuss end-toend solution designs and testbed implementations, we present the key security and privacy challenges associated with the sensitive nature of medical data and we summarize the most recent research projects dedicated to e-Health applications. Index TermsMachine-to-Machine (M2M), e-Health, WBAN, M2M Area Network, M2M Communications Network, IEEE 802.15.6, end-to-end communications

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Power- and delay-awareness of health telemonitoring services: the mobihealth system case study

Cited by 23 publications

References 21 publications

Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care

Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care

A Survey on M2M Systems for mHealth: A Wireless Communications Perspective

Machine-to-machine (M2M) communications for e-health applications

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