Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 195

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Body area network for wireless patient monitoring

Montón, E., Hernandez, J.F., Blasco, J.M., Hervé, T., Micallef, J., Grech, I., Brincat, A., Traver, V.·2008·IET Communications

Abstract

Patient data monitoring is a key issue for health and disease management. The use of wireless sensors within a body area network (BAN) makes this task seamless and easy. A BAN system is presented, which allows the connectivity of a wide range of heterogeneous body sensors to a portable hub device that is connectable to external networks (IEEE 802.11, GPRS). This BAN is based on the use of Zigbee/IEEE 802.15.4 standard technology and off-the-shelf modules. It is currently being used at the European level for the detection and the prediction of the human physiological state in relation to wakefulness, fatigue, and stress applications in which users carrying out daily activities are monitored in an unobtrusive and comfortable way. Characterised by its low power consumption, low cost, and ability to connect a wide range of heterogeneous sensors, this system can substantially improve the performance of different services, especially those that are health related.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1049/iet-com:20070046

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 1 references

Cited by

See all 195

Metadata

Authors
Montón, E., Hernandez, J. F., Blasco, J. M., Hervé, T., Micallef, J., Grech, I., Brincat, A., & Traver, V.
Venue
IET Communications
Published
2008-02
Volume
2
Issue
2
Pages
215-222
ISSN
  • 1751-8628 (ISSN-L)
  • 1751-8636
OpenAlex
W2026623061
Cited by
195
References
1
FWCI
11.30
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: Body area network for wireless patient monitoring. https://app.cochat.ai/papers/10.1049/iet-com:20070046
The paper
Montón, E., Hernandez, J. F., Blasco, J. M., Hervé, T., Micallef, J., Grech, I., Brincat, A., & Traver, V. (2008). Body area network for wireless patient monitoring. IET Communications. https://doi.org/10.1049/iet-com%3A20070046

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.