Wireless Body Area Networks: A Survey

By S. Movassaghi, Mehran Abolhasan, Justin Lipman, David B. Smith, Abbas Jamalipour. IEEE Communications Surveys and Tutorials, 2014

1,491 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4ed4d6b28a8d9a5c410eef2e2921f2a37433c272

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Lajos Hanzo
2. Shahaboddin Shamshirband
3. Valerio Persico
4. Antonio Pescapè
5. Giuseppe Aceto
6. Sumit Majumder

In Electrical and Electronic Engineering

1. Shaoshi Yang
2. Zesong Fei
3. JingJing Wang
4. Lajos Hanzo
5. Chunxiao Jiang
6. Shahaboddin Shamshirband
7. Bin Li
8. Haijun Zhang

Citations in the corpus

• Survey of main challenges (security and privacy) in wireless body area networks for healthcare applications (2017, background): “In fact, security, privacy and Quality of Service (QoS) need to be assessed [67,68].”
• Survey on 6G Frontiers: Trends, Applications, Requirements, Technologies and Future Research (2021, neutral): “detection, entertainment, and secure authentication applications [149].”
• Cryptanalysis and Improvement of Anonymous Authentication for Wireless Body Area Networks with Provable Security (2020, background): “Wireless body area networks (WBANs) is an emerging e-monitoring technology that allows real-time monitoring of patient health remotely [1].”
• Semantic Communications for Future Internet: Fundamentals, Applications, and Challenges (2022, neutral): “physical objects with a high level of realism rivaling of the physical presence [176], [190].”
• Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks (2019, background): “In [233], Abouzar et al. proposed an action-based network association technique for wireless body area networks (WBANs).”
• Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0 (2020, background): “IoT • enhanced electromedical devices (closed-loop design, predictive maintenance, new service lines) [131] • interoperability, evolvability thanks to open communication standards [132] • energy constraints [133] • security [134, 135, 136, 81, 137, 138].”
• Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges (2017, background): “For instance, the cell phone of a diabetic patient can detect the glucose and send it to a doctor for analysis [33].”
• A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems (2016, background): “), acting as an in vitro or in vivo diagnostic system [60].”