A Real-Time Cardiac Monitoring using a Multisensory Smart IoT System

Majumder, Akm Jahangir Alam; Elsaadany, Mohammed; Izaguirre, Joshua Aaron; Ucci, D.R.

doi:10.1109/compsac.2019.10220

Cited by 9 publications

(4 citation statements)

References 14 publications

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“…Using a MAX30100 pulse oximeter, the authors in [ 20 ] collected heart beat information. The publications [ 21 , 22 , 23 ] utlized an ECG module AD8232 to obtain the patients heart rate data in real time for monitoring purposes. Table 5 mentions recent studies on heart rate sensors.…”

Section: Discussionmentioning

confidence: 99%

“…ECG is the most crucial biological parameter for monitoring, detecting, predicting, and classifying cardiac irregularities and variations in the human heart. The ECG AD8232 module was used in the studies [ 21 , 22 , 38 , 39 , 40 ] to monitor ECG and detect cardiac anomalies in cardiovascular patients. Heart abnormalities were detected with the use of the ECG AD8233 module [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

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%

Section: Discussionmentioning

confidence: 99%

E-Cardiac Care: A Comprehensive Systematic Literature Review

Umar

Nayab

Irfan

et al. 2022

Sensors

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“…Fingerprint [75], [76], [77], palmprint [78] and iris/gaze [79], [80] are mainly used for user's identification tasks due to their uniqueness for each person. EEG [81], [82], [83], EGG, respiratory [84], [85], [86], heart rate [87], [88], [89] are used for the user's state monitoring. Besides the fact that they can provide valuable information, their usage in real applications is difficult to be applied due to the special wearable devices that it is required for the capturing.…”

Section: Human Centric Perceptionmentioning

confidence: 99%

Empowering cyberphysical systems of systems with intelligence

Nousias¹,

Piperigkos²,

Arvanitis³

et al. 2021

Preprint

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Cyber Physical Systems have been going into a transition phase from individual systems to a collecttives of systems that collaborate in order to achieve a highly complex cause, realizing a system of systems approach. The automotive domain has been making a transition to the system of system approach aiming to provide a series of emergent functionality like traffic management, collaborative car fleet management or large-scale automotive adaptation to physical environment thus providing significant environmental benefits (e.g air pollution reduction) and achieving significant societal impact. Similarly, large infrastructure domains, are evolving into global, highly integrated cyber-physical systems of systems covering all parts of the value chain. In practice, there are significant challenges in CPSoS applicability and usability to be addressed, i.e. even a small CPSoS such as a car consists several subsystems Decentralization of CPSoS appoints tasks to individual CPSs within the System of Systems. CPSoSs are heterogenous systems. They comprise of various, autonomous, CPSs, each one of them having unique performance capabilities, criticality level, priorities and pursued goals. all CPSs must also harmonically pursue systembased achievements and collaborate in order to make system-ofsystem based decisions and implement the CPSoS functionality. This survey will provide a comprehensive review on current best practices in connected cyberphysical systems. The basis of our investigation is a dual layer architecture encompassing a perception layer and a behavioral layer. Perception algorithms with respect to scene understanding (object detection and tracking, pose estimation), localization mapping and path planning are thoroughly investigated. Behavioural part focuses on decision making and human in the loop control.

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“…The survival rate for the sudden cardiac arrest is low. It is possible to save 60% human life by continuously monitoring the fitness of the person [1]. In recent times, the Internet of Things (IoT) is emerging as one of the promising technologies.…”

Section: Introductionmentioning

confidence: 99%

Edge Computing Based Cardiac Monitoring and Detection System in the Internet of Medical Things

Murugesan,

Naganathan

2024

MEDIN

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Currently, cardiac disease becomes one of the major health issues in the world. The death due to cardiac arrests has been increasing day by day. The survival rate for the sudden cardiac arrest is low. It is possible to save 60% human life by continuously monitoring the fitness of the person. In recent times, the Internet of Things is emerging promising technologies. If the doctor cannot monitor the patient face to face, there Internet of Things plays important role in remotely monitoring the patient’s condition. With the rise in the use of smart wearable gadgets, the contribution of IoT will be more. In this paper, about five predictor model are analyzed for a particular dataset and chosen the best as Random forest algorithm. The proposed system integrates oxygen saturation level and heart rate sensor data from MAX30100 sensor for monitoring the patient’s vital signs. The remaining parametric data of the patient (AGE, GENDER, BLOOD SUGAR LEVEL, BLOOD PRESSURE LEVEL, GENETIC ISSUE and CHLOESTEROL LEVEL) are fed through the matrix keypad. The designed system monitors the online patient’s vitals continuously. The patient’s vitals will be stored in the edge server and also analyzed. The chosen predictor model checks the vital data for any abnormality and based on abnormality data detection in the heart rate, the warning message is conveyed to the nearby health care center via Thingspeak cloud. By tracking the patient’s GPS location, the server cloud sends alert notification along with the GPS location to the nearby health center and to the registered mobile numbers.

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A Real-Time Cardiac Monitoring using a Multisensory Smart IoT System

Cited by 9 publications

References 14 publications

E-Cardiac Care: A Comprehensive Systematic Literature Review

E-Cardiac Care: A Comprehensive Systematic Literature Review

Empowering cyberphysical systems of systems with intelligence

Edge Computing Based Cardiac Monitoring and Detection System in the Internet of Medical Things

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