2021
DOI: 10.3390/electronics10212719
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IoT and Cloud Computing in Health-Care: A New Wearable Device and Cloud-Based Deep Learning Algorithm for Monitoring of Diabetes

Abstract: Diabetes is a chronic disease that can affect human health negatively when the glucose levels in the blood are elevated over the creatin range called hyperglycemia. The current devices for continuous glucose monitoring (CGM) supervise the glucose level in the blood and alert user to the type-1 Diabetes class once a certain critical level is surpassed. This can lead the body of the patient to work at critical levels until the medicine is taken in order to reduce the glucose level, consequently increasing the ri… Show more

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Cited by 63 publications
(34 citation statements)
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“…The authors evaluated their system on 112 subjects and the implementation of RNN achieved an accuracy of 82.14% in tracking blood glucose levels into four classes. A recent study also assessed the ability to estimate future (i.e., 30 min prediction horizon) blood glucose levels using an IoT device with CGM sensor, an application layer protocol, and prediction model on the cloud ( Nasser et al, 2021 ). Based on a model consisting of RNNs and restricted boltzmann machines, the proposed system achieved an RMSE value of 15.59 mg/dl in data acquired from ten patients with type 1 diabetes.…”
Section: Machine Learning Techniquesmentioning
confidence: 99%
“…The authors evaluated their system on 112 subjects and the implementation of RNN achieved an accuracy of 82.14% in tracking blood glucose levels into four classes. A recent study also assessed the ability to estimate future (i.e., 30 min prediction horizon) blood glucose levels using an IoT device with CGM sensor, an application layer protocol, and prediction model on the cloud ( Nasser et al, 2021 ). Based on a model consisting of RNNs and restricted boltzmann machines, the proposed system achieved an RMSE value of 15.59 mg/dl in data acquired from ten patients with type 1 diabetes.…”
Section: Machine Learning Techniquesmentioning
confidence: 99%
“…For monitoring, wearable devices can automatically and continuously collect users' physiological (e.g., temperature, heart rate, respiration rate, and blood pressure) or biochemical indicators (e.g., sweat), monitor the health condition of the human body, and detect physical movements [11,13], activities [9] and contextual information through wearable sensors [18,19], which can be used in various fields such as healthcare [14], fitness, sports, robotics, administration, education [15], and the military. For example, Apple Watch is a popular wearable device that incorporates many fitness and health data tracking functions.…”
Section: Classification Of Wearable Technology and Devicesmentioning
confidence: 99%
“…Wearable technology is worn in various forms such as earphones [8], gloves [9], watches, e-textiles, pastes [10], smart tags [11] and glasses [12]. They are widely used in health care [13,14], virtual/augmented reality [12], robotics, teleoperation, education [15], and sports or even for everyday use [10]. With a combination of wearable devices and mobile apps, it is possible to measure personal PM2.5 concentration data and provide useful activity guidelines based on real-time data [16].…”
Section: Introductionmentioning
confidence: 99%
“…The World Health Organization (WHO) has reported that 15 million people worldwide have suffered strokes and 5 million have been left disabled for a long time. The main causes of acute and long-term disabilities are neurological injuries such as strokes, heart attacks and spinal cord injuries (SCIs) [1].…”
Section: Introductionmentioning
confidence: 99%