Cloud-based health monitoring framework using smart sensors and smartphone

Subaşı, Abdülhamit; Bandić, Lejla; Qaisar, Saeed Mian

doi:10.1016/b978-0-12-819043-2.00009-5

Cited by 12 publications

(4 citation statements)

References 65 publications

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“…The results showed that the implementation, even with an increased number of devices, has been able to scale successfully in dealing with health data without losing performance effectiveness as revealed by stable rate of query performance as the number of data sources and packets increase. Similarly, Subasi, Bandic [90] proposed a cloud-based framework for fast real-time analysis of heterogenous ECG and electroencephalogram (EEG) data streamed from smart biomedical sensors and smartphones. The framework was designed by combining adaptive signal acquisition, segmentation and denoising to optimize the signal transmission rate.…”

Section: Big Data-based Methodsmentioning

confidence: 99%

Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

et al. 2022

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Electrocardiography (ECG) is one of the most widely used recordings in clinical medicine. ECG deals with the recording of electrical activity that is generated by the heart through the surface of the body. The electrical activity generated by the heart is measured using electrodes that are attached to the body surface. The use of ECG in the diagnosis and management of cardiovascular disease (CVD) has been in existence for over a decade, and research in this domain has recently attracted large attention. Along this line, an expert system (ES) and decision support system (DSS) have been developed for ECG interpretation and diagnosis. However, despite the availability of a lot of literature, access to recent and more comprehensive review papers on this subject is still a challenge. This paper presents a comprehensive review of the application of ES and DSS for ECG interpretation and diagnosis. Researchers have proposed a number of features and methods for ES and DSS development that can be used to monitor a patient’s health condition through ECG recordings. In this paper, a taxonomy of the features and methods for ECG interpretation and diagnosis were presented. The significance of the features and methods, as well as their limitations, were analyzed. This review further presents interesting theoretical concepts in this domain, as well as identifies challenges and open research issues on ES and DSS development for ECG interpretation and diagnosis that require substantial research effort. In conclusion, this paper identifies important future research areas with the purpose of advancing the development of ES and DSS for ECG interpretation and diagnosis.

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Section: Big Data-based Methodsmentioning

confidence: 99%

Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

et al. 2022

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“…Cloud-based health monitoring frameworks, leveraging smart technologies, showcase the integration of wearables and cloud computing into promising healthcare techniques [12]. The synergy of the cloud and the IoT significantly influences remote healthcare, enhancing patient outcomes and monitoring capabilities [13].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Remote Patient Monitoring: A Review of Biosensors Integrated with Multi-Hop IoT Systems via Cloud Connectivity

Uddin,

Koo

2024

Applied Sciences

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This comprehensive review paper explores the intricate integration of biosensors with multi-hop Internet of Things (IoT) systems, representing a paradigm shift in healthcare through real-time remote patient monitoring. The strategic deployment of biosensors in different locations in medical facilities, intricately connected to multiple microcontrollers, serves as a cornerstone in the establishment of robust multi-hop IoT networks. This paper highlights the role of this multi-hop IoT network, which efficiently facilitates the seamless transmission of vital health data to a centralized server. Crucially, the utilization of cloud connectivity emerges as a linchpin in this integration, providing a secure and scalable platform for remote patient monitoring. This cloud-based approach not only improves the accessibility of critical health information but also transcends physical limitations, allowing healthcare providers to monitor patients in real-time from any location. This paper highlights the transformative potential of this integration in overcoming traditional healthcare limitations through real-time remote patient monitoring.

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“…Next-generation communication technologies accelerated the adoption of smartphones as the primary medium for consumer interactions (Steen, 2009; Kim and Park, 2016). Smartphones provide technology convergence of internet, camera, microphone, location sensors, orientation sensors, fingerprint and other biometric sensors, among others (Gábor and Gausz, 2018; Astriani et al , 2019; Roobini and Fenila Naomi, 2019; Söderlund et al , 2019; Subasi et al , 2019; Sukariasih et al , 2019; Petrescu et al , 2020). This technology convergence is one of the key contributing factors making smartphones the preferred target for genuine and malicious actors.…”

Section: Introductionmentioning

confidence: 99%

Consumer privacy in smartphones: a systematic literature review

R.,

Shome,

Shankar

et al. 2023

JCM

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Purpose This study aims to provide a systematic review of consumer privacy literature in the context of smartphones and undertake a comprehensive analysis of academic research on this evolving research area. Design/methodology/approach This review synthesises antecedents, consequences and mediators reported in consumer privacy literature and presents these factors in a conceptual framework to demonstrate the consumer privacy phenomenon. Findings Based on the synthesis of constructs reported in the existing literature, a conceptual framework is proposed highlighting antecedents, mediators and outcomes of experiential marketing efforts. Finally, this study deciphers overlooked areas of consumer privacy in the context of smartphone research and provides insightful directions to advance research in this domain in terms of theory development, context, characteristics and methodology. Originality/value This study significantly contributes to consumer behaviour literature, specifically consumer privacy literature.

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Cloud-based health monitoring framework using smart sensors and smartphone

Cited by 12 publications

References 65 publications

Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions

Real-Time Remote Patient Monitoring: A Review of Biosensors Integrated with Multi-Hop IoT Systems via Cloud Connectivity

Consumer privacy in smartphones: a systematic literature review

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