ReviewSensors (Basel, Switzerland)2019
Systematic Analysis of a Military Wearable Device Based on a Multi-Level Fusion Framework: Research Directions.
Review in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Triboelectric Nanogenerators in Military: Recent Progress and Critical Challenges.Nano-micro letters · 2026Review
- Tactical-Grade Wearables and Authentication Biometrics.Sensors (Basel, Switzerland) · 2026Review
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- Real-Time Anomaly Detection in Physiological Parameters: A Multi-Squad Monitoring and Communication Architecture.Sensors (Basel, Switzerland) · 2025Article
- Advances in Wearable Biosensors for Healthcare: Current Trends, Applications, and Future Perspectives.Biosensors · 2024Review
- Research on the Human Motion Recognition Method Based on Wearable.Biosensors · 2024Article
- Optimising Combat Readiness: Practical Strategies for Integrating Physiological and Psychological Resilience in Soldier Training.Healthcare (Basel, Switzerland) · 2024Article
- The Influence of the Washing Process on the Impedance of Textronic Radio Frequency Identification Transponder Antennas.Materials (Basel, Switzerland) · 2023Article
- Deep-Learning-Based Context-Aware Multi-Level Information Fusion Systems for Indoor Mobile Robots Safe Navigation.Sensors (Basel, Switzerland) · 2023Article
- Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review.JMIR mHealth and uHealth · 2022Article
- A Survey on Wireless Wearable Body Area Networks: A Perspective of Technology and Economy.Sensors (Basel, Switzerland) · 2022Review
- Applications and Innovations on Sensor-Enabled Wearable Devices.Sensors (Basel, Switzerland) · 2022Article
- Article
- Evaluating consumer and clinical sleep technologies: an American Academy of Sleep Medicine update.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2021Article
- Review
- Recent Advances in Noninvasive Biosensors for Forensics, Biometrics, and Cybersecurity.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
With the development of the Internet of Battlefield Things (IoBT), soldiers have become key nodes of information collection and resource control on the battlefield. It has become a trend to develop wearable devices with diverse functions for the military. However, although densely deployed wearable sensors provide a platform for comprehensively monitoring the status of soldiers, wearable technology based on multi-source fusion lacks a generalized research system to highlight the advantages of heterogeneous sensor networks and information fusion. Therefore, this paper proposes a multi-level fusion framework (MLFF) based on Body Sensor Networks (BSNs) of soldiers, and describes a model of the deployment of heterogeneous sensor networks. The proposed framework covers multiple types of information at a single node, including behaviors, physiology, emotions, fatigue, environments, and locations, so as to enable Soldier-BSNs to obtain sufficient evidence, decision-making ability, and information resilience under resource constraints. In addition, we systematically discuss the problems and solutions of each unit according to the frame structure to identify research directions for the development of wearable devices for the military.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.