A wireless blood sugar monitoring system using ion-sensitive Field Effect Transistor

Perez, Jason M. Dy; Misa, Windel B.; Tan, Patrick; Yap, Roderick; Robles, Julita C.

doi:10.1109/tencon.2016.7848317

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…More investigation is needed to get beyond the sensor's contamination exposure constraint. Wireless body area networks are optimal for transmitting glucose estimations (WBAN) [11]. A patient's caregivers can monitor their progress through a web website or mobile device.…”

Section: Review Of Literaturementioning

confidence: 99%

Glucose Monitoring with AI Analytics for Diabetes Management Using Machine Learning and Smart Devices

Contreras,

Vehi

2023

IJANER

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Over the past few years, there has been a noticeable growth in the usage of smart devices for diabetes treatment. These technologies are meant to make life easier for people with diabetes because they have the potential to improve the stability of blood sugar monitoring and predict the onset of dangerous episodes (hypo/hyperglycemia). Notwithstanding, the primary goals of diabetic self-management are to enhance the lifestyle and quality of life of those living with the disease. This study used the literature that addressed diabetes to conduct a systematic review to monitor and control the disease effectively. The search was narrowed to include topical keywords like Artificial Intelligence (AI), technology, self-management, and diabetes, for which PubMed databases were used. There were 2655 papers in all, released between 2013 and 2023. Predicting blood glucose, identifying risk events early, automatically adjusting insulin dosages, and other diabetes care issues are the main goals of most of the chosen research. Wearable technology and AI methods were combined in these investigations. Much scientific attention has been drawn to wearable technology like Continuous Glucose Monitoring (CGM) in treating chronic illnesses like diabetes. Not only may they help avoid diabetes-related problems, but they can also aid in managing diabetes. Utilizing these gadgets has also enhanced the quality of life and treatment of sickness.

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Section: Review Of Literaturementioning

confidence: 99%

Glucose Monitoring with AI Analytics for Diabetes Management Using Machine Learning and Smart Devices

Contreras,

Vehi

2023

IJANER

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“…In [17], the authors proposed a design that employees an ion-sensitive field-effect transistor which is connected to a microcontroller. The readings are sent to a doctor through a Wi-Fi module.…”

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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