An IoT System for Remote Health Monitoring in Elderly Adults through a Wearable Device and Mobile Application

Durán-Vega, Luis A.; Santana-Mancilla, Pedro C.; Buenrostro-Mariscal, Raymundo; Contreras-Castillo, Juan; Anido‐Rifón, Luis E.; García-Ruiz, Miguel Á.; Montesinos‐López, Osval A.; Estrada-González, Fermín

doi:10.3390/geriatrics4020034

Cited by 84 publications

(47 citation statements)

References 19 publications

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“…These findings are a great incentive for future developments. With respect to systems that monitor older adults, an IoT system for heart rate, body temperature, and blood oxygenation was presented in [30]. Although glucose was not considered in the monitoring, the importance of the IoT system and the mobile application were emphasized.…”

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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Section: Related Workmentioning

confidence: 99%

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

et al. 2020

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“…Smart geriatric nursing for physical health should be based on IoT technologies. In detail, the smart nursing strategies include but should be not limited to the following: Biosensor-based real-time monitoring and remote management of geriatric physical activities and vital signs [ 28 – 31 ] Medication safety and management with smart technologies including RFID, sensor, electronic tag, two-dimension code, and global positioning system (GPS) [ 32 – 36 ] Smart assessment of geriatric cognitive function with online and offline methods [ 37 – 40 ], e.g., estimating the influence of healthy lifestyle on episodic memory among adults who have subjective memory complaints [ 40 ] Smart nursing methods for geriatric common and chronic diseases [ 41 – 43 ] …”

Section: Smart Geriatric Nursing In Physical Healthmentioning

confidence: 99%

“…Biosensor-based real-time monitoring and remote management of geriatric physical activities and vital signs [ 28 – 31 ]…”

Section: Smart Geriatric Nursing In Physical Healthmentioning

confidence: 99%

A Simple Framework of Smart Geriatric Nursing considering Health Big Data and User Profile

Tang

2020

Computational and Mathematical Methods in Medicine

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The National Bureau of Statistics of China shows that the population over 65 years old in China exceeds 166 million accounting for 11.93% of the total population by the end of 2018. The importance and severity of taking care of the elderly are becoming increasingly prominent. High-quality and meticulous care for the daily life of the elderly needs helpful and advanced sciences and technologies. Smart geriatric nursing is a must. Basing on the professional knowledge of geriatric nursing, this paper proposes a framework of smart geriatric nursing which consists of three aspects of smart nursing: smart geriatric nursing in physical health using biosensor and advanced devices, smart geriatric nursing in mental health based on user profile, and smart geriatric nursing for daily life based on big data in health. The deployment of the proposed method relies on the technologies of the Internet of Things (IoT), user profile system, big data, and many other advanced information technologies. The framework of methods can provide a useful reference for the systematic technical scheme of smart geriatric nursing in an aging society.

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“…The IoT is recognized by healthcare industries as the most important technology in the future [5]. In fact, centralized health monitoring services focused on IoT can help the safety and ease of elderly people who can't access to healthcare services [6].…”

Section: Introductionmentioning

confidence: 99%

A Secure Framework for Authentication and Encryption Using Improved ECC for IoT-Based Medical Sensor Data

et al. 2020

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Mobile users are increasing exponentially to adopt ubiquitous services offered by various sectors. This has attracted attention for a secure communication framework to access e-health data on mobile devices. The wearable sensor device is attached to the patient's body which monitors the blood pressure, body temperature, serum cholesterol, glucose level, etc. In the proposed secure framework, first, the task starts with the patient authentication, after that the sensors device linked to the patient is activated and the sensor values of the patient are transmitted to the cloud server. The patient's biometrics information has been added as a parameter in addition to the user name and password. The authentication scheme is coined with the SHA-512 algorithm that ensures integrity. To securely send the sensor information, the method follows two kinds of encryption: Substitution-Ceaser cipher and improved Elliptical Curve Cryptography (IECC). Whereas in improved ECC, an additional key (secret key) is generated to enhance the system's security. In this way, the intricacy of the two phases is augmented. The computational cost of the scheme in the proposed framework is 4H + Ec + Dc which is less than the existing schemes. The average correlation coefficient value is about 0.045 which is close to zero shows the strength of the algorithm. The obtained encryption and decryption time are 1.032 µs and 1.004µs respectively. The overall performance is analyzed by comparing the proposed improved ECC with existing Rivest-Shamir-Adleman (RSA)and ECC algorithms.

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An IoT System for Remote Health Monitoring in Elderly Adults through a Wearable Device and Mobile Application

Cited by 84 publications

References 19 publications

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications

A Simple Framework of Smart Geriatric Nursing considering Health Big Data and User Profile

A Secure Framework for Authentication and Encryption Using Improved ECC for IoT-Based Medical Sensor Data

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