Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 291

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

A Universal high accuracy wearable pulse monitoring system via high sensitivity and large linearity graphene pressure sensor

He, Jiang, Xiao, Peng, Lu, Wei, Shi, Jiangwei, Zhang, Ling, Liang, Yun, Pan, Caofeng, Kuo, Shiao-Wei, Chen, Tao·2019·Nano Energy

Abstract

Abstract Long-term accurate pulse monitoring can provide much physiological parameter information in a non-invasive way. A versatile pressure sensor with high sensitivity over a wide linear range (up to 10 kPa) is thus especially desired for this purpose. However, the trade-off between linearity region and sensitivity has not been well balanced. Despite micro/nanostructure morphologies, our simulation and mechanism analyses found that a thinner structure and better conductivity property of the sensing layer contribute to a larger linearity range and higher sensitivity, respectively. However, these two properties are often difficult to achieve simultaneously in one traditional material. Herein, a novel material design strategy is developed to fabricate a self-assembled graphene sensing film, in which the conductivity and thickness can be well balanced. As a result, our sensor exhibits unprecedented comprehensive properties with both high sensitivity (1875.53 kPa−1) and wide linear detection range (0–40 kPa). The sensor is also endowed with good stability and high peak signal-noise ratio (78 dB). Taking advantages of these performances, a universal high accuracy wireless and wearable pulse monitoring system was built. This platform first provides the subtle arterial pulse signal information even under the interference of strong body movement in real-time (during running or cycling), which could not have been realized before. This wearable system is expected to provide more rich and accurate information for personalized diagnostic applications in the future.

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 · 10.1016/j.nanoen.2019.02.036

Cites

5 of 5 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 5 references

Cited by

See all 291

Metadata

Authors
He, J., Xiao, P., Lu, W., Shi, J., Zhang, L., Liang, Y., Pan, C., Kuo, S.-W., & Chen, T.
Venue
Nano Energy
Publisher
Elsevier BV
Published
2019-05
Volume
59
Pages
422-433
ISSN
2211-2855 (ISSN-L)
OpenAlex
W2914336498
Cited by
291
References
5
FWCI
12.02
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: A Universal high accuracy wearable pulse monitoring system via high sensitivity and large linearity graphene pressure sensor. https://app.cochat.ai/papers/10.1016/j.nanoen.2019.02.036
The paper
He, J., Xiao, P., Lu, W., Shi, J., Zhang, L., Liang, Y., Pan, C., Kuo, S.-W., & Chen, T. (2019). A Universal high accuracy wearable pulse monitoring system via high sensitivity and large linearity graphene pressure sensor. Nano Energy. https://doi.org/10.1016/j.nanoen.2019.02.036

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.