The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The design of an m-Health monitoring system based on a cloud computing platform
Abstract
Compared to traditional medical services provided within hospitals, m-Health monitoring systems (MHMSs) face more challenges in personalised health data processing. To achieve personalised and high-quality health monitoring by means of new technologies, such as mobile network and cloud computing, in this paper, a framework of an m-Health monitoring system based on a cloud computing platform (Cloud-MHMS) is designed to implement pervasive health monitoring. Furthermore, the modules of the framework, which are Cloud Storage and Multiple Tenants Access Control Layer, Healthcare Data Annotation Layer, and Healthcare Data Analysis Layer, are discussed. In the data storage layer, a multiple tenant access method is designed to protect patient privacy. In the data annotation layer, linked open data are adopted to augment health data interoperability semantically. In the data analysis layer, the process mining algorithm and similarity calculating method are implemented to support personalised treatment plan selection. These three modules cooperate to implement the core functions in the process of health monitoring, which are data storage, data processing, and data analysis. Finally, we study the application of our architecture in the monitoring of antimicrobial drug usage to demonstrate the usability of our method in personal healthcare analysis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Internet of Things in industries: A survey
Xu, L. D., He, W., & Li, S. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2300753 · Cited by 5,172
Context Aware Computing for The Internet of Things: A Survey
Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2013.042313.00197 · Cited by 2,861 · cited 1×
“The wide usages of emerging mobile Internet and Internet of Things (IoT) in industries have changed the way that information is acquired, stored, accessed, and delivered (He and Xu 2015; Xu, He, and Li 2014; Perera et al. 2014).”
BackgroundEMG and EPP-integrated human-machine interface between the paralyzed and rehabilitation exoskeleton
Yin, Y. H., Fan, Y. J., & Xu, L. D. (2012) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2011.2178034 · Cited by 197
Self-citationMobile health in emerging countries: A survey of research initiatives in Brazil
Iwaya, L. H., Gomes, M. A. L., Simplício, M. A., Carvalho, T. C. M. B., Dominicini, C. K., Sakuragui, R. R. M., Rebelo, M. S., Gutierrez, M. A., Näslund, M., & Håkansson, P. (2013) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2013.01.003 · Cited by 88
Cited by
Industry 4.0: state of the art and future trends
Xu, L. D., Xu, E. L., & Li, L. (2018) · International Journal of Production Research · doi:10.1080/00207543.2018.1444806 · Cited by 3,221
Self-citationA Survey on Internet of Things and Cloud Computing for Healthcare
Dang, L. M., Piran, M. J., Han, D., Min, K., & Moon, H. (2019) · Electronics · doi:10.3390/electronics8070768 · Cited by 640
Yu, H., Yang, L. T., Zhang, Q., Armstrong, D., & Deen, M. J. (2021) · Neurocomputing · doi:10.1016/j.neucom.2020.04.157 · Cited by 412
Cloud-centric IoT based disease diagnosis healthcare framework
Verma, P., & Sood, S. K. (2018) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2017.11.018 · Cited by 246
Recent patient health monitoring platforms incorporating internet of things-enabled smart devices
Kang, M., Park, E., Cho, B. H., & Lee, K.-S. (2018) · International Neurourology Journal · doi:10.5213/inj.1836144.072 · Cited by 143
Metadata
- Authors
- Xu, B., Xu, L., Cai, H., Jiang, L., Luo, Y., & Gu, Y.
- Venue
- Enterprise Information Systems
- Publisher
- Informa UK Limited
- Published
- 2015-06-15
- Volume
- 11
- Issue
- 1
- Pages
- 17-36
- ISSN
- 1751-7575 (ISSN-L)
- 1751-7583
- OpenAlex
- W2205445074
- Cited by
- 177
- References
- 4
- FWCI
- 25.12
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The design of an m-Health monitoring system based on a cloud computing platform. https://app.cochat.ai/papers/10.1080/17517575.2015.1053416
- The paper
- Xu, B., Xu, L., Cai, H., Jiang, L., Luo, Y., & Gu, Y. (2017). The design of an m-Health monitoring system based on a cloud computing platform. Enterprise Information Systems. https://doi.org/10.1080/17517575.2015.1053416
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.