Review of Smart Health Monitoring Approaches With Survey Analysis and Proposed Framework

Gahlot, Sonal; Reddy, S. R. N.; Kumar, Dinesh

doi:10.1109/jiot.2018.2872389

Cited by 65 publications

(26 citation statements)

References 31 publications

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“…It has been commonly recognized as the Internet of Things is used as a possible solution to relieve the stresses on healthcare infrastructures and has become a prominent research issue in recent times [47]- [49]. Health monitoring can be ensured through wearable sensors and smartphone applications.…”

Section: Healthcare Monitoring Devices In Iotmentioning

confidence: 99%

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Mahmoud¹,

et al. 2021

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The significant increase in the number of individuals with chronic ailments (including the elderly and disabled) has dictated an urgent need for an innovative model for healthcare systems. The evolved model will be more personalized and less reliant on traditional brick-and-mortar healthcare institutions such as hospitals, nursing homes, and long-term healthcare centers. The smart healthcare system is a topic of recently growing interest and has become increasingly required due to major developments in modern technologies, especially in artificial intelligence (AI) and machine learning (ML). This paper is aimed to discuss the current state-of-the-art smart healthcare systems highlighting major areas like wearable and smartphone devices for health monitoring, machine learning for disease diagnosis, and the assistive frameworks, including social robots developed for the ambient assisted living environment. Additionally, the paper demonstrates software integration architectures that are very significant to create smart healthcare systems, integrating seamlessly the benefit of data analytics and other tools of AI. The explained developed systems focus on several facets: the contribution of each developed framework, the detailed working procedure, the performance as outcomes, and the comparative merits and limitations. The current research challenges with potential future directions are addressed to highlight the drawbacks of existing systems and the possible methods to introduce novel frameworks, respectively. This review aims at providing comprehensive insights into the recent developments of smart healthcare systems to equip experts to contribute to the field.

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Section: Healthcare Monitoring Devices In Iotmentioning

confidence: 99%

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Mahmoud¹,

et al. 2021

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“…It's been implemented among and a few were demonstrated in practice to detect the harmful gas but both approaches were effective gas sensing units have been implemented which is capable of detecting the harmful and toxic gases individually and display in the LCD. Harmful gases like carbon monoxide, Methane, Hydrogen Sulphide these gases are very toxic to the human, Heart Beat sensor this may be fixed on the worker's hand watch and the message is going to be sent to outside workers and Municipal Officers with the assistance of IoT [4].…”

Section: Introductionmentioning

confidence: 99%

Cascading of Air Quality Detector and Digital Data Transmission with Zero Error in Minimum Duration

Anitha¹,

Veerasundaram²,

Rajarajan³

et al. 2021

Recent Trends in Intensive Computing

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The paper proposes a system to monitor the environment air quality using an Arduino microcontroller, to enhance the quality IOT Technology is used. The utilization of IoT technology improves the method of monitoring various factors of the environment issues. The MQ-02 gas sensor is used to detect the various gases which are harmful to humans. A Wi-Fi module connects the whole system to the internet and an LCD is employed for the visual Output. This Automated Air management system may be a breakthrough to contribute an answer to the most important threat. The air quality detector overcomes the problems of the highly polluted areas which may be a major issue. This technique has features for the user to monitor the quantity of pollution on their smart devices using the appliance.

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“…The gradual popularization of Wi-Fi networks has made Wi-Fi networks and the Internet a rapidly developing area [26]- [28]. Multi-network fusion technology will be more and more favored by research experts [29], [30]. Relevant scholars have studied the family intimate nurse system [31]- [33].…”

Section: Introductionmentioning

confidence: 99%

Health Monitoring of Human Multiple Physiological Parameters Based on Wireless Remote Medical System

Zhang

Ling

2020

IEEE Access

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Telemedicine, as a new technical means and medical model, can truly realize the sharing and monitoring of telemedicine information, and ultimately ensure that everyone has equal access to medical and health resources. Based on the research on the status of telemedicine application and wireless communication technology, this paper proposes a multi-physical parameter wireless telemedicine health monitoring system solution, and analyzes the overall structure and functional requirements of the system. Human physiological parameters of the wireless remote medical system for health monitoring include body temperature, respiration, blood oxygen saturation, pulse, blood pressure, and electrocardiogram. In this paper, fabric electrodes are used to extract human bioimpedance signals, discrete Fourier transform algorithm is used to detect human respiratory signals, and respiratory rate is detected based on dynamic differential threshold peak detection technology. The reflection type photoelectric sensor is used to realize the reflection of the human pulse signal, and the continuous measurement of the cuff-free blood pressure based on the pulse wave conduction time is combined with the ECG (Electrocardiogram) data. A self-learning threshold algorithm based on near-infrared photo plethysmo graphy signal trough detection is designed on the reflective blood oxygen saturation calculation algorithm. The difference threshold method is used to extract the QRS band feature points. We tested the overall operation of the system. The results show that the collected human physiological signal data is accurate. After a series of tests, the validity and reliability of the collected physiological signals have been proven. INDEX TERMS Telemedicine, health monitoring, physiological signals, signal processing.

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Review of Smart Health Monitoring Approaches With Survey Analysis and Proposed Framework

Cited by 65 publications

References 31 publications

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospects

Cascading of Air Quality Detector and Digital Data Transmission with Zero Error in Minimum Duration

Health Monitoring of Human Multiple Physiological Parameters Based on Wireless Remote Medical System

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