Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,075

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

Flexible Sensing Electronics for Wearable/Attachable Health Monitoring

Wang, Xuewen, Liu, Zheng, Zhang, Ting·2017·Small

Abstract

Wearable or attachable health monitoring smart systems are considered to be the next generation of personal portable devices for remote medicine practices. Smart flexible sensing electronics are components crucial in endowing health monitoring systems with the capability of real‐time tracking of physiological signals. These signals are closely associated with body conditions, such as heart rate, wrist pulse, body temperature, blood/intraocular pressure and blood/sweat bio‐information. Monitoring such physiological signals provides a convenient and non‐invasive way for disease diagnoses and health assessments. This Review summarizes the recent progress of flexible sensing electronics for their use in wearable/attachable health monitoring systems. Meanwhile, we present an overview of different materials and configurations for flexible sensors, including piezo‐resistive, piezo‐electrical, capacitive, and field effect transistor based devices, and analyze the working principles in monitoring physiological signals. In addition, the future perspectives of wearable healthcare systems and the technical demands on their commercialization are briefly discussed.

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 · 10.1002/smll.201602790

Cites

40 of 40 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 40 references

Cited by

See all 1,075

Metadata

Authors
Wang, X., Liu, Z., & Zhang, T.
Venue
Small
Publisher
Wiley
Published
2017-03-17
Volume
13
Issue
25
ISSN
  • 1613-6810 (ISSN-L)
  • 1613-6829
OpenAlex
W2596867090
Cited by
1,075
References
40
FWCI
44.11
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: Flexible Sensing Electronics for Wearable/Attachable Health Monitoring. https://app.cochat.ai/papers/10.1002/smll.201602790
The paper
Wang, X., Liu, Z., & Zhang, T. (2017). Flexible Sensing Electronics for Wearable/Attachable Health Monitoring. Small. https://doi.org/10.1002/smll.201602790

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.