Evidence map›Paper›PMID 40566767›Full record

ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2025

[Performance evaluation of a wearable steady-state visual evoked potential based brain-computer interface in real-life scenario].

Xiaodong Li, Xiang Cao, Junlin Wang, Weijie Zhu, Yong Huang, Feng Wan, Yong Hu

Abstract readEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2025. 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
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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

7 authors.

Xiaodong LiShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, P. R. China.
Xiang CaoDepartment of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong S. A. R. 999077, P. R. China.
Junlin WangOrthopedic Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong 518053, P. R. China.
Weijie ZhuJoint Lab of Brain-Verse Digital Convergence, Guangdong Institute of Intelligence Science and Technology, Zhuhai, Guangdong 519060, P. R. China.
Yong HuangSchool of Biomedical Engineering, Southern Medical University, Guangzhou 510515, P. R. China.
Feng WanDepartment of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau S. A. R. 999078, P. R. China.
Yong HuOrthopedic Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong 518053, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain-computer interface (BCI) has high application value in the field of healthcare. However, in practical clinical applications, convenience and system performance should be considered in the use of BCI. Wearable BCIs are generally with high convenience, but their performance in real-life scenario needs to be evaluated. This study proposed a wearable steady-state visual evoked potential (SSVEP)-based BCI system equipped with a small-sized electroencephalogram (EEG) collector and a high-performance training-free decoding algorithm. Ten healthy subjects participated in the test of BCI system under simplified experimental preparation. The results showed that the average classification accuracy of this BCI was 94.10% for 40 targets, and there was no significant difference compared to the dataset collected under the laboratory condition. The system achieved a maximum information transfer rate (ITR) of 115.25 bit/min with 8-channel signal and 98.49 bit/min with 4-channel signal, indicating that the 4-channel solution can be used as an option for the few-channel BCI. Overall, this wearable SSVEP-BCI can achieve good performance in real-life scenario, which helps to promote BCI technology in clinical practice.

Indexed as

Brain-Computer InterfacesElectroencephalographyEvoked Potentials, VisualWearable Electronic DevicesAdultAlgorithmsHumansMaleSignal Processing, Computer-AssistedBrain-computer interfaceSimplified experimental preparationSteady-state visual evoked potentialWearable system

Identifiers

PMID40566767
PMCPMC12236208

What OpenQuestion holds

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Read underepoch 390

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.