The Cardiac Disease Predictor: IoT and ML Driven Healthcare System

Tabassum, Shaira; Zaman, Md. Ittahad Uz; Ullah, Md. Sabbir; Rahaman, Ashikur; Nahar, Samsun; Islam, A.K.M. Muzahidul

doi:10.1109/eict48899.2019.9068821

Cited by 16 publications

(6 citation statements)

References 10 publications

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“…In 2017 [ 29 ], a digital BP monitor (OMRONHBP1300) was used to monitor and automatically detect cardiac arrhythmia. The paper published in 2019 [ 30 ] examined predicting cardiac ailments in E-Cardiology using ECG, cholesterol, and BP. The MPX10 BP sensor was utilised in the 2020 publication [ 27 ] for patient health monitoring.…”

Section: Discussionmentioning

confidence: 99%

E-Cardiac Care: A Comprehensive Systematic Literature Review

Umar

Nayab

Irfan

et al. 2022

Sensors

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The Internet of Things (IoT) is a complete ecosystem encompassing various communication technologies, sensors, hardware, and software. IoT cutting-edge technologies and Artificial Intelligence (AI) have enhanced the traditional healthcare system considerably. The conventional healthcare system faces many challenges, including avoidable long wait times, high costs, a conventional method of payment, unnecessary long travel to medical centers, and mandatory periodic doctor visits. A Smart healthcare system, Internet of Things (IoT), and AI are arguably the best-suited tailor-made solutions for all the flaws related to traditional healthcare systems. The primary goal of this study is to determine the impact of IoT, AI, various communication technologies, sensor networks, and disease detection/diagnosis in Cardiac healthcare through a systematic analysis of scholarly articles. Hence, a total of 104 fundamental studies are analyzed for the research questions purposefully defined for this systematic study. The review results show that deep learning emerges as a promising technology along with the combination of IoT in the domain of E-Cardiac care with enhanced accuracy and real-time clinical monitoring. This study also pins down the key benefits and significant challenges for E-Cardiology in the domains of IoT and AI. It further identifies the gaps and future research directions related to E-Cardiology, monitoring various Cardiac parameters, and diagnosis patterns.

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Section: Discussionmentioning

confidence: 99%

E-Cardiac Care: A Comprehensive Systematic Literature Review

Umar

Nayab

Irfan

et al. 2022

Sensors

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“…When testing the system, the accuracy reached 96.20% as it recognized all nine gestures tested. Tabassum et al [62] proposed a system for heart disease prediction. The required data were collected using sensors such as a cholesterol sensor, blood pressure sensor, heart rate sensor, glucose sensor, and electrocardiography sensor.…”

Section: And Iotmentioning

confidence: 99%

Blockchain and machine learning in the internet of things: a review of smart healthcare

Al-Blihed

Al-Mufadi²,

Al-Harbi³

et al. 2023

IJ-AI

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<span lang="EN-US">The healthcare sector has benefited from digital transformation and modern technology. As well is expected to rely even more on the internet of things (IoT) technologies in the near future. Due to the availability of portable medical devices, applications, and mobile health services, all of which have contributed to the development of innovative features for the delivery of healthcare services. With the large number of data issued from the IoT and the importance of using data to benefit from contained in diagnosing diseases, medical records, or monitoring. Furthermore, the expansion of emerging technologies such as robots and machine learning (ML) is supported by the ease with exchanged and shared medical information. Moreover, Blockchain technology enables the creation of secure records for storing medical data in a safe and timely manner. The paper reviews various IoT, Blockchain, and ML applications and systems in the smart healthcare sector to discover many challenges, consequently, it will be easy for researchers who have an interest in these fields to find today and future solutions. This, in turn, will help to enhance the technical services depending on the IoT in ML and Blockchain in the smart healthcare field.</span>

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“…Figure 5 depicts many sensors integrated to detect physiological data from the human body, such as ECG, EEG, GPS, BT, BP, glucose measurement, and so on. Studies such as Tabassum, et al [ 113 ] and Magaña-Espinoza, et al [ 114 ] successfully utilized smartphones to gather data from the human body. In the Communication layer, the sensor data gathered are transported to the network storage level using different protocols and technologies.…”

Section: Iot Frameworkmentioning

confidence: 99%

Recent Advancements in Emerging Technologies for Healthcare Management Systems: A Survey

et al. 2022

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In recent times, the growth of the Internet of Things (IoT), artificial intelligence (AI), and Blockchain technologies have quickly gained pace as a new study niche in numerous collegiate and industrial sectors, notably in the healthcare sector. Recent advancements in healthcare delivery have given many patients access to advanced personalized healthcare, which has improved their well-being. The subsequent phase in healthcare is to seamlessly consolidate these emerging technologies such as IoT-assisted wearable sensor devices, AI, and Blockchain collectively. Surprisingly, owing to the rapid use of smart wearable sensors, IoT and AI-enabled technology are shifting healthcare from a conventional hub-based system to a more personalized healthcare management system (HMS). However, implementing smart sensors, advanced IoT, AI, and Blockchain technologies synchronously in HMS remains a significant challenge. Prominent and reoccurring issues such as scarcity of cost-effective and accurate smart medical sensors, unstandardized IoT system architectures, heterogeneity of connected wearable devices, the multidimensionality of data generated, and high demand for interoperability are vivid problems affecting the advancement of HMS. Hence, this survey paper presents a detailed evaluation of the application of these emerging technologies (Smart Sensor, IoT, AI, Blockchain) in HMS to better understand the progress thus far. Specifically, current studies and findings on the deployment of these emerging technologies in healthcare are investigated, as well as key enabling factors, noteworthy use cases, and successful deployments. This survey also examined essential issues that are frequently encountered by IoT-assisted wearable sensor systems, AI, and Blockchain, as well as the critical concerns that must be addressed to enhance the application of these emerging technologies in the HMS.

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The Cardiac Disease Predictor: IoT and ML Driven Healthcare System

Cited by 16 publications

References 10 publications

E-Cardiac Care: A Comprehensive Systematic Literature Review

E-Cardiac Care: A Comprehensive Systematic Literature Review

Blockchain and machine learning in the internet of things: a review of smart healthcare

Recent Advancements in Emerging Technologies for Healthcare Management Systems: A Survey

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