Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 769

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

Wearable Sensors‐Enabled Human–Machine Interaction Systems: From Design to Application

Yin, Ruiyang, Wang, Depeng, Zhao, Shufang, Lou, Zheng, Shen, Guozhen·2021·Advanced Functional Materials

Abstract

In comparison to traditional bulky and rigid electronic devices, the human–machine interaction (HMI) system with flexible and wearable components is an inevitable future trend. To achieve effective, intuitive, and seamless manipulation of high‐performance wearable HMI systems, it is important to develop effective strategies for designing material microstructures on flexible sensors and electric devices with excellent mechanical flexibility and stretchability. The real‐time acquisition of human physiology and surrounding signals through accurate and flexible sensors is the basis of wearable HMIs. Herein, the construction of a wearable HMI system that utilizes sensors, communication modes, and actuators is reviewed. The mechanisms and strategies for designing various flexible sensors based on different mechanisms are analyzed and discussed. The functional mechanism, material selection, and novel design strategies of each part are summarized in detail. The different communication modes in interactive systems and the manufacturing technology of soft machines are also introduced. Additionally, the most advanced applications of wearable HMI systems in intelligent identification and security, interactive controls for robots, augmented reality, and virtual reality have been highlighted. The review concludes with an overview of the remaining key challenges and several ideas regarding the further improvement of wearable HMI systems.

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/adfm.202008936

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 769

Metadata

Authors
Yin, R., Wang, D., Zhao, S., Lou, Z., & Shen, G.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2020-12-29
Volume
31
Issue
11
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W3117266371
Cited by
769
References
40
FWCI
21.16
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: Wearable Sensors‐Enabled Human–Machine Interaction Systems: From Design to Application. https://app.cochat.ai/papers/10.1002/adfm.202008936
The paper
Yin, R., Wang, D., Zhao, S., Lou, Z., & Shen, G. (2021). Wearable Sensors‐Enabled Human–Machine Interaction Systems: From Design to Application. Advanced Functional Materials. https://doi.org/10.1002/adfm.202008936

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.