BlockTheFall: Wearable Device-based Fall Detection Framework Powered by Machine Learning and Blockchain for Elderly Care
Author:
Affiliation:
1. Kennesaw State University,Department of Information Technology,Georgia,United States
2. Kennesaw State University,Department of Information Systems and Security,Georgia,United States
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10196792/10196808/10196872.pdf?arnumber=10196872
Reference15 articles.
1. A comparative study on HIPAA technical safeguards assessment of android mHealth applications
2. Coalition of 6G and Blockchain in AR/VR Space: Challenges and Future Directions
3. Mobile Sensor-Based Fall Detection Framework
4. Towards decentralized IoT security enhancement: A blockchain approach
5. Sector Diversity among IT Professionals in the Timing of Blockchain Adoption: An Attitudinal Perspective
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4. A Radar-Based System for Detection of Human Fall Utilizing Analog Hardware Architectures of Decision Tree Model;IEEE Open Journal of Circuits and Systems;2024
5. Social Governance and Sustainable Development in Elderly Services: Innovative Models, Strategies, and Stakeholder Perspectives;Sustainability;2023-10-30
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