Internet of Things (IoT) Based ECG System for Rural Health Care

Rahman, Md. Obaidur; Kashem, Mohammod Abul; Nayan, Al-Akhir; Akter, Most. Fahmida; Rabbi, Fazly; Ahmed, Marzia; Asaduzzaman, Mohammad

doi:10.14569/ijacsa.2021.0120653

Cited by 11 publications

(6 citation statements)

References 20 publications

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“…The hypertext transfer protocol (HTTP) and message queuing telemetry transport (MQTT) servers are all deployed in the cloud environment to give consumers rapid and simple ECG data retrieval. The collected information is processed in a non-relational database, allowing for improvements in data storage velocity and versatility [26]. A web based application is designed and developed for the medical professionals to evaluate the cardiac problems of the patients using ECG data acquired by sensors.…”

Section: Research Methods Of Iot-based Ecg Monitoring Systemmentioning

confidence: 99%

Internet of things based electrocardiogram monitoring system using machine learning algorithm

Rahman

Shamrat

Kashem

et al. 2022

IJECE

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<span>In Bangladesh’s rural regions, almost 30% of the population lives in poverty. Rural residents also have restricted access to nursing and diagnostic services due to obsolete healthcare infrastructure. Consequently, as cardiac failure occurs, they usually fail to call the services and adopt the facilities. The internet of things (IoT) offers a massive advantage in addressing cardiac problems. This study proposed a smart IoT-based electrocardiogram (ECG) monitoring system for heart patients. The system is divided into several parts: ECG sensing network (data acquisition), IoT cloud (data transmission), result analysis (data prediction) and monetization. P, Q, R, S, and T are ECG signal properties fetched, pre-processed, analyzed and predicted to age level for future health management. ECG data are saved in the cloud and accessible via message queuing telemetry transport (MQTT) and hypertext transfer protocol (HTTP) servers. The linear regression method is utilized to determine the impact of electrocardiogram signal characteristics and error rate. The prediction was made to see how much variation there was in PQRST regularity and its sufficiency to be utilized in an ECG monitoring device. Recognizing the quality parameter values, acceptable outcomes are achieved. The proposed system will diminish future medical costs and difficulties for heart patients.</span>

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Section: Research Methods Of Iot-based Ecg Monitoring Systemmentioning

confidence: 99%

Internet of things based electrocardiogram monitoring system using machine learning algorithm

Rahman

Shamrat

Kashem

et al. 2022

IJECE

Self Cite

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“…Integration of DL architectures and machine learning (ML) algorithms are mislaid here. IoT-based ECG monitoring systems have added a new dimension to this field [16]- [19]. Most of the studies focused on signal acquisition where data preprocessing is a major concern.…”

Section: Literature Reviewmentioning

confidence: 99%

A cost-effective ECG monitoring in rural areas: leveraging artificial neural networks for efficient healthcare solutions

Rahaman,

Kashem

2024

Bulletin EEI

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Cardiovascular diseases engender serious public health concerns in developing nations since access to specialized medical equipment is often limited and standard treatment expenses can be prohibitive. This study proposes an efficient and relatively affordable electrocardiogram (ECG) monitoring system that reads and analyzes a person's electrocardiogram data to provide affordable and quality healthcare solutions. The device initially extracts features from electrocardiogram records by reading electrical signals in the heart. Extracted data are then analyzed by a trained deep learning model to determine precisely if the heart is in a healthy state or undergoing complexities. Experimental results showed that the fine-tuned ANN architecture outperformed the state-of-the-art architectures in this field with an accuracy of 98.95%. The data can also be sent to specialists through an MQTT server if necessary, allowing for remote diagnosis and treatment. The system is intended to be deployed in countries where rural regions lack access to specialized healthcare equipment and professionals. Additionally, the device is inexpensive and, hence can be made accessible to people with limited affordability.

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“…The future of aquaculture food production needs to face a lot of challenges among them the preservation of water quality, cost effectiveness, food quality and space utility [99], but one of the most important is waste compound usage which is important to transform the system into a sustainable production method [130]. Nowadays, different and new technologies are helping to transform aquaculture food production with the use of sensors, artificial intelligent models [132] or the introduction of the Internet of Thinks to make production management easier [133]. Wastewater treatment is one of the most important aspects and the future lies in the capacity to remove a high quantity of residues by using different biofilter and recirculation systems [134,135] with different plants and aquatic animals to evade damaging nutrients discharges into the environment [118].…”

Section: Groundwater Usage and The Environmental Impact In Aquacultur...mentioning

confidence: 99%

Horticulture Irrigation Systems and Aquaculture Water Usage: A Perspective for the Use of Aquaponics to Generate a Sustainable Water Footprint

Schoor,

Arenas-Salazar,

Parra-Pacheco

et al. 2024

Preprint

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The expansion of food production is getting more important due to a rising world population, which is relying on food security on a regional and local scale. Intensive food production systems create a negative impact on the regional ecosystem because of agrochemical pollution and nutrient rich water discharges into nearby rivers. Furthermore, these systems are highly depending on regional water resources causing water scarcity and soil erosion due to the overexploitation of natural resources in general. The objective of this article is to review the water usage in the two most water intensive food production systems, agriculture and aquaculture showing lacking areas, like system management and climate change, which must be considered in the implementation of sustainable water footprint. In addition, the review includes an analysis if the combination of both production system into aquaponic food production and the possibilities of water saving. There are a variety of water footprint analyses for crop and aquatic animal production, but there is also a lack of information about the system management including irrigation systems, system cleaning processes, water substitution, pond removal, evaporation due to climate change and especially in aquaculture, the water footprint of industrial elaborated fish feed.

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Internet of Things (IoT) Based ECG System for Rural Health Care

Cited by 11 publications

References 20 publications

Internet of things based electrocardiogram monitoring system using machine learning algorithm

Internet of things based electrocardiogram monitoring system using machine learning algorithm

A cost-effective ECG monitoring in rural areas: leveraging artificial neural networks for efficient healthcare solutions

Horticulture Irrigation Systems and Aquaculture Water Usage: A Perspective for the Use of Aquaponics to Generate a Sustainable Water Footprint

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