FDRF: Fault Detection and Recovery Framework for Seamless Data Transmission in Remote Health Monitoring Using WBAN

Karmakar, Koushik; Saif, Sohail; Das, P. Sarati; Neogy, Sarmistha; Biswas, Suparna

doi:10.1007/s11277-021-09134-3

Wireless Pers Commun

2021

DOI: 10.1007/s11277-021-09134-3

|View full text |Cite

FDRF: Fault Detection and Recovery Framework for Seamless Data Transmission in Remote Health Monitoring Using WBAN

Koushik Karmakar¹,

Sohail Saif

P. Sarati Das³

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

An optimized back propagation neural network for automated evaluation of health condition using sensor data

Mandala,

Senthilnathan,

Suganyadevi

et al. 2023

Measurement: Sensors

View full text Add to dashboard Cite

An optimized back propagation neural network for automated evaluation of health condition using sensor data

Mandala,

Senthilnathan,

Suganyadevi

et al. 2023

Measurement: Sensors

View full text Add to dashboard Cite

Systematic Review of IoT-Based Solutions for User Tracking: Towards Smarter Lifestyle, Wellness and Health Management

Amini Gougeh,

Zilic

2024

Sensors

View full text Add to dashboard Cite

The Internet of Things (IoT) base has grown to over 20 billion devices currently operational worldwide. As they greatly extend the applicability and use of biosensors, IoT developments are transformative. Recent studies show that IoT, coupled with advanced communication frameworks, such as machine-to-machine (M2M) interactions, can lead to (1) improved efficiency in data exchange, (2) accurate and timely health monitoring, and (3) enhanced user engagement and compliance through advancements in human–computer interaction. This systematic review of the 19 most relevant studies examines the potential of IoT in health and lifestyle management by conducting detailed analyses and quality assessments of each study. Findings indicate that IoT-based systems effectively monitor various health parameters using biosensors, facilitate real-time feedback, and support personalized health recommendations. Key limitations include small sample sizes, insufficient security measures, practical issues with wearable sensors, and reliance on internet connectivity in areas with poor network infrastructure. The reviewed studies demonstrated innovative applications of IoT, focusing on M2M interactions, edge devices, multimodality health monitoring, intelligent decision-making, and automated health management systems. These insights offer valuable recommendations for optimizing IoT technologies in health and wellness management.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

FDRF: Fault Detection and Recovery Framework for Seamless Data Transmission in Remote Health Monitoring Using WBAN

Cited by 2 publications

References 38 publications

An optimized back propagation neural network for automated evaluation of health condition using sensor data

An optimized back propagation neural network for automated evaluation of health condition using sensor data

Systematic Review of IoT-Based Solutions for User Tracking: Towards Smarter Lifestyle, Wellness and Health Management

Contact Info

Product

Resources

About