Evidence map›Paper›PMID 41788543›Full record

ReviewFrontiers in neuroscience2026

Evoked potentials in stroke rehabilitation: current applications, emerging technologies, and future directions.

Zhe Wang, Xiaolin Liu, Jingyang Xie, Yujun Lin

Abstract readReview
In one paragraph

Review in Frontiers in neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Zhe WangLaboratory of Neuroelectrophysiology, Yantai Yantaishan Hospital, Yantai, China.
Xiaolin LiuDepartment of Neurology, Zibo 148 Hospital, China RongTong Medical Healthcare Group Co. Ltd., Zibo, China.
Jingyang XieLaboratory of Electrophysiology, Yantai Yantaishan Hospital, Yantai, China.
Yujun LinLaboratory of Neuroelectrophysiology, Yantai Yantaishan Hospital, Yantai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evoked potentials (EPs) are increasingly explored as objective neurophysiological biomarkers to complement scale-based assessment in stroke rehabilitation. This narrative review summarizes current evidence on the use of somatosensory evoked potentials (SEPs), motor evoked potentials (MEPs), and event-related potentials (ERPs) for monitoring recovery and guiding therapy. We first outline the physiological basis and stroke-relevant features of each modality, then synthesize data on how EP measures relate to motor, sensory, balance, cognitive and language outcomes, with particular emphasis on longitudinal changes during rehabilitation and responses to specific interventions, including neuromuscular electrical stimulation, robot-assisted training and non-invasive brain stimulation. Emerging applications such as perturbation-evoked cortical responses for postural control, EP-based brain-computer interfaces and EP-guided or closed-loop neuromodulation are discussed, together with advances in high-density recordings, connectivity analysis, and machine-learning-based multimodal prediction models. Finally, we highlight key methodological and practical challenges-protocol heterogeneity, small single-center studies, limited trial evidence, feasibility constraints and gaps in clinical integration-and propose priorities for standardization and translational research. Overall, EPs hold substantial promise as pathway-specific, temporally precise biomarkers to enable more mechanism-informed and individualized stroke rehabilitation monitoring.

Indexed as

ERPsevoked potentialsMEPsSEPsstroke

Identifiers

PMID41788543
PMCPMC12956785

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.