An elderly health monitoring system based on biological and behavioral indicators in internet of things

Hosseinzadeh, Mehdi; Koohpayehzadeh, Jalil; Ghafour, Marwan Yassin; Ahmed, Aram Mahmood; Asghari, Parvaneh; Souri, Alireza; Pourasghari, Hamid; Rezapour, Aziz

doi:10.1007/s12652-020-02579-7

Cited by 38 publications

(15 citation statements)

References 30 publications

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“…Classification is required to identify the level of potential risks of physiological and behavioral changes in the elderly. Experimental results confirm that the SMO, MLP, and NB classifiers perform almost closely in terms of accuracy, precision, sensitivity, and F-measure [40]. This method tries to prioritize the data sensed in the IoT network and does not pay attention to the quality of service parameters.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 62%

Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective‐Based Multiagent Approach

Javid

Mirzaei

2021

Wireless Communications and Mobile Computing

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Developments in information and related technologies have led to a wider use of the Internet of things (IoT). By integrating both virtual and physical worlds, IoT creates an integrated communication framework of interrelated things and operating systems. With the advent of IoT systems based on digital remote care, transferring medical data is becoming a daily routine. Healthcare is one of the most popular IoT applications and tries to monitor patients’ vital signs during the day for weeks and to eliminate the need for hospitalization. In a healthcare system, many sensors are installed to collect the patient’s information, including environmental monitoring sensors and vital and unstructured message sensors in order to reduce the patients’ expenses. The IoT network contains flexible sensors in dynamically changing environments where sensors collect environmental information and send it to nursing stations for healthcare applications. Due to the wireless nature of IoT networks, secure data transmission in the healthcare context is very important. Data collected from sensors embedded in healthcare devices may be lost for various reasons along the transmission path. Therefore, establishing a secure communication path in IoT networks in the context of healthcare is of great importance. In this paper, in order to provide a reliable data transfer protocol in the context of healthcare, a reliable routing using multiobjective genetic algorithm (RRMOGA) method is presented. The contribution of this paper can be summarized in two steps: (i) using a multiobjective optimization approach to find near-optimal paths and (ii) using reliable agents in the network to find backup paths. The simulation outcomes reveal that the proposed approach, based on the use of the multiobjective optimization approach, tries to find optimal paths for information transfer that improve the main parameters of the network. Also, the use of secure agents leads to a secure information transfer in the network in the context of healthcare. Experimental results show that the proposed method has achieved reliability and data delivery rates, 99% and 99.9%, respectively. The proposed method has improved network lifetime, delivery rate, and delay by 14%, 2%, and 5.6%, respectively.

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Section: Wireless Communications and Mobile Computingmentioning

confidence: 62%

Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective‐Based Multiagent Approach

Javid

Mirzaei

2021

Wireless Communications and Mobile Computing

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“…However, IoT and cloud computing-based healthcare technologies now support physicians in offering great healthcare services and real-time applications. 45 Due to the efficient communications between patients and doctors, the engagement and satisfaction of patients have been increased. This has resulted in a reduction in the duration of hospital stay and the avoidance of hospital readmissions.…”

Section: Healthcare Concepts and Applicationsmentioning

confidence: 99%

Cloud healthcare services: A comprehensive and systematic literature review

Rahimi

Navimipour

Hosseinzadeh

et al. 2022

Trans Emerging Tel Tech

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Over the last decade, the landscape of cloud computing has been significantly changed. It has been known as a paradigm in which a shared pool of computing resources is accessible for users. The rapid growth of the healthcare environment provides better medical services to reduce costs and increase competition among healthcare providers. Despite its crucial role in the cloud, no thorough study exists in this domain. This article presents a systematic study for healthcare services in the cloud environment. A well‐organized overview of all the databases has been explored. By clustering the research goals of the found papers, we have derived four main research groups. We have further evaluated the papers concerning the background of the paper, QoS parameters, application area, or methods used for applying and formulating the main ideas presented in the works. This survey emphasizes the challenges, needs, benefits of using cloud computing in healthcare systems and provides a comprehensive and detailed study on cloud healthcare services, strengths, and weaknesses of the existing methods. Highlighting cloud health services can be the major focus of research for developing the urban healthcare system.

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“…The system was able to respond in minimal time and with a higher level of accuracy. In 2020, Hosseinzadeh et al [14] proposed a health monitoring system for elderly patients based on the Internet of Things. The system was capable of remotely monitoring the patient's health by sensing their biologic and behavioral parameters through IoT devices embedded in the patient's proximity.…”

Section: Iot Enabled Health Monitoring Systemsmentioning

confidence: 99%

Early Urine Infection Prediction Framework using XGBoost Ensemble Model in IoT-Fog Environment

Gupta

Singh

2022

Preprint

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Urine infections are one of the most prevalent concerns for the healthcare industry that may impair the functioning of the kidney and other renal organs. As a result, early diagnosis and treatment of such infections are essential to avert any future complications. Conspicuously, in the current work, an intelligent system for the early prediction of urine infections has been presented. The proposed framework uses IoTbased sensors for data collection, followed by data encoding and Infectious Risk Factor computation using the XGBoost algorithm over the fog computing platform. Finally, the analysis results along with the healthrelated information of users are stored in the cloud repository for future analysis. For performance validation, extensive experiments have been carried out and results are calculated based on real-time patients’ data. The statistical results of accuracy(91.45%), specificity(95.96%), sensitivity(84.79%), precision(95.49%), and f-score(90.12%) reveal the significantly improved performance of the proposed strategy over other baseline techniques.

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An elderly health monitoring system based on biological and behavioral indicators in internet of things

Cited by 38 publications

References 30 publications

Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective‐Based Multiagent Approach

Presenting a Reliable Routing Approach in IoT Healthcare Using the Multiobjective‐Based Multiagent Approach

Cloud healthcare services: A comprehensive and systematic literature review

Early Urine Infection Prediction Framework using XGBoost Ensemble Model in IoT-Fog Environment

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