Mobile health platform for diabetes management based on the Internet-of-Things

Al-Taee, Majid A.; Al-Nuaimy, Waleed; Al-Ataby, Ali; Muhsin, Zahra J.; Abood, Suhail N.

doi:10.1109/aeect.2015.7360551

Cited by 59 publications

(27 citation statements)

References 16 publications

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“…A few articles adopted a case-control [19,41,42,50,54] or randomized control research design [16,28,56]. For some articles [11,18,21,23,24,58], information provided on how the experiments were conducted was not sufficient for determining the research design adopted.…”

Section: Qualitative Synthesismentioning

confidence: 99%

“…Surprisingly, the Cardiovascular diseases [20,23] were conducted solely with healthy participants while another [21] and three of the sub-studies in [21,22] lack information on whether the participants were healthy or patients. Regarding Diabetes and Nutrition, two works [24,28] were conducted with patients, one study [27] was conducted with healthy participants while two articles [25,26] lack this information. Finally, regarding Stress and sleep, none of the studies report on studies with patients.…”

Section: Tests On Patients and Healthy Usersmentioning

confidence: 99%

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A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

Kristoffersson

Lindén

2020

Sensors

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The use of wearable body sensors for health monitoring is a quickly growing field with the potential of offering a reliable means for clinical and remote health management. This includes both real-time monitoring and health trend monitoring with the aim to detect/predict health deterioration and also to act as a prevention tool. The aim of this systematic review was to provide a qualitative synthesis of studies using wearable body sensors for health monitoring. The synthesis and analysis have pointed out a number of shortcomings in prior research. Major shortcomings are demonstrated by the majority of the studies adopting an observational research design, too small sample sizes, poorly presented, and/or non-representative participant demographics (i.e., age, gender, patient/healthy). These aspects need to be considered in future research work.

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Section: Qualitative Synthesismentioning

confidence: 99%

Section: Tests On Patients and Healthy Usersmentioning

confidence: 99%

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

Kristoffersson

Lindén

2020

Sensors

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“…The developed testbed prototype is still open for further improvements and applications in various fields including self-management of chronic diseases and delivery of healthcare services over a distance using e/m-health platforms (Al-Taee et al, 2015, 2016a, 2016b.…”

Section: Resultsmentioning

confidence: 99%

A testbed for experimental evaluation of efficient multimedia delivery over lossy networks

Al-Taee¹,

Ala'²,

Khalifeh³

et al. 2017

IJDSSS

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Abstract:Multimedia transmission over lossy networks has been rapidly increasing, especially with the advent of different high-speed and cost-effective Internet technologies. Despite these technology advances, however, the quality of video streaming over lossy networks is still a major challenge towards obtaining the best quality of service. In this paper, a new experimental testbed that is based on the real-time media flow protocol (RTMFP) is proposed to enable researchers to investigate and optimise the effect of changing multiple key parameters relevant to the video-streaming quality. The impact of these parameters, which include video resolution, frames per second, and compression rate on the video quality are investigated with various settings of network packet loss. The obtained results and relationships between these parameters have led to development of a new algorithm that is capable of changing the parameters under study, in real time, according to the estimated packet loss towards maximum obtainable quality. Design details and experimental setup of the proposed testbed are presented along with key practical considerations and experimental evaluation results.

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“…The IoT is proposed as a good environment for diabetes management in [22]. Smartphones are proposed for remote collection and monitoring of data, with feedback for the patient and medical caregivers.…”

Section: Telemedicinementioning

confidence: 99%

Towards an ICT-Based Platform for Type 1 Diabetes Mellitus Management

2018

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Type 1 Diabetes Mellitus (DM1) is a metabolic disease that is characterized by chronic hyperglycemia due to a lack of pancreatic insulin production. This forces patients to perform several blood glucose measurements per day-by means of capillary glucometers-in order to infer a trend and try to predict future values. In this way, a decision about the insulin dosage that has to be exogenously injected to maintain glycemia within the desirable levels is made. Unfortunately, this method usually suffers from relatively high imprecision. However, recent advances in information and communication technologies (ICT), along with novel biosensors that could provide a real-time comprehensive condition of the patient, offer a new perspective in DM1 management. In this sense, new disruptive technologies like Big Data, the Internet of Things (IoT), and Cloud Computing, as well as Machine Learning (ML) can play an important role in managing DM1. In this work, firstly, an analysis of previously published ICT-based methods for the management of diabetes continuous monitoring is carried out. In this way, an assessment of the possible lack of such proposals is presented, along with the challenges to be overcome in forthcoming smart DM1 management systems. Finally, an overview of a holistic ICT-based platform for DM1 management that try to solve the limitations of previous works, while at the same time, taking advantage of the abovementioned disruptive technologies is hereby proposed.Appl. Sci. 2018, 8, 511 2 of 15 either by multiple daily injections or by continuous infusion, using a pump, which permeates under the skin.In this context, new technological possibilities offer a new horizon in diabetes management. Although the first steps towards an artificial pancreas (AP) were undertaken 50 years ago [1], when the concept of a computer-supported system emulating the behavior of a pancreas by using a control algorithm was introduced, promising that technological advances achieved in recent years are supposed to bring a revolution in this field. Nowadays, an AP (which has not been completely achieved yet) is presumed to be composed of a Continuous Glucose-Monitoring (CGM) device aimed at checking the patient's glucose levels in real time (a feature that is already available) and injecting (a feature that is not yet commercially available) insulin (and glucagon, if applicable) into his or her body, along with a control system based on a closed loop, which must decide the amount of hormone (insulin or glucagon) to be injected [2,3].2017 was a particularly significant year regarding the AP [4]. Clinical trials were performed and their results were published, showing a good performance under real and demanding situations. Even a commercial hybrid closed-loop system is commercially available at present, Medtronic MiniMed 670G, which automatically adjusts basal insulin every five minutes based on CGM readings and is able to stop insulin up to 30 min before reaching a preset low limit. It also automatically restarts insulin when patient's lev...

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Mobile health platform for diabetes management based on the Internet-of-Things

Cited by 59 publications

References 16 publications

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

A testbed for experimental evaluation of efficient multimedia delivery over lossy networks

Towards an ICT-Based Platform for Type 1 Diabetes Mellitus Management

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