Evidence map›Paper›PMID 42220613›Full record

ReviewMaterials today. Bio2026

Source-level motion artifact suppression in wearable electrodes: From underlying mechanisms to advanced strategies.

Haizhou Huang, Xuanjing Cai, Shu Wan, Litao Sun

Abstract readReview
In one paragraph

Review in Materials today. Bio, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Haizhou HuangCollege of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, 350117, PR China.
Xuanjing CaiCollege of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, 350117, PR China.
Shu WanKey Laboratory of Optoelectronic Technology and Systems, Ministry of Education, Key Disciplines Laboratory of Novel Micro-Nano Devices and System Technology, School of Optoelectronics Engineering, Chongqing University, Chongqing, 400044, PR China.
Litao SunSEU-FEI Nano-Pico Center, Key Laboratory of MEMS of Ministry of Education, Collaborative Innovation Center for Micro/Nano Fabrication, Device and System, Southeast University, Nanjing, 210096, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motion artifacts (MAs) significantly degrade the quality of surface biopotential signals acquired in dynamic environments (such as during body movements), severely compromising their reliable application in health monitoring and disease diagnosis. Although various post-processing methods have been reported to mitigate MAs, they often entail inherent limitations (such as signal distortion, latency, and incomplete artifact removal), highlighting the necessity of suppressing MAs at their source. This review provides an in-depth analysis of the mechanisms underlying MA generation and systematically summarizes source-level MAs suppression strategies based on innovations in electrode materials and structures. These strategies mainly include skin-anchoring strategy, deformation constraint strategy, strain-insensitive strategy and damping strategy. By stabilizing the skin-electrode interface and mitigating mechanical interference, they significantly reduce the occurrence of artifacts. The advantages and challenges of these strategies are further evaluating and future prospects toward achieving motion-artifact-free biopotential dynamic recording are also discussed. This review offers a clear framework and direction for the design of high-performance electrophysiological electrodes tailored for dynamic applications.

Indexed as

ElectrodesElectrophysiological signalsMotion artifactMotion noise removal

Identifiers

PMID42220613
PMCPMC13218256

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.