Evidence map›Paper›PMID 42197993›Full record

ArticleSensors (Basel, Switzerland)2026

Design and Experimental Investigation of a Multi-Level Heartbeat Sound Feedback-Based Neurofeedback System: Neural Mechanisms.

Xiuyan Hu, Mingge Kang, Yijing Liu, Ting Shi, Xinyu Shi, Yunfa Fu, Anmin Gong

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

7 authors.

Xiuyan HuCollege of Information Engineering, Chinese People's Armed Police Force Engineering University, Xi'an 710086, China.
Mingge KangCollege of Information Engineering, Chinese People's Armed Police Force Engineering University, Xi'an 710086, China.
Yijing LiuCollege of Information Engineering, Chinese People's Armed Police Force Engineering University, Xi'an 710086, China.
Ting ShiCollege of Information Engineering, Chinese People's Armed Police Force Engineering University, Xi'an 710086, China.
Xinyu ShiCollege of Information Engineering, Chinese People's Armed Police Force Engineering University, Xi'an 710086, China.
Yunfa FuSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Anmin GongCollege of Information Engineering, Chinese People's Armed Police Force Engineering University, Xi'an 710086, China.ORCID 0000-0002-2715-2296

Funding

China Postdoctoral Science Foundation 2023M734315National Natural Science Foundation of China 62006246, 82172058, 62376112, 81771926, 61763022the Xi'an Science and Technology Association Youth Talent Support Program 959202413100
6 · The paper itself

Abstract

Auditory neurofeedback training (NFT) based on brain-computer interfaces (BCIs) has recently entered the precision motor domain as a task-embedded neural state regulation paradigm. Compared to traditional standalone NFT approaches (e.g., relaxation or attention training designed to enhance general cognitive abilities), task-embedded paradigms integrate feedback directly into the motor task execution process. However, this design inevitably creates a dual-task scenario, and the effects of such a scenario on neural activity and behavioral performance have received limited systematic investigation in the existing literature. This study designed and implemented a closed-loop BCI system employing five-level heartbeat sound feedback and used this system as a research platform to examine the immediate neural mechanism changes and potential dual-task interference effects induced by single-session auditory NFT in moderately skilled shooters. The system maps real-time EEG features onto graded auditory signals varying in playback rate and volume intensity, incorporating a dynamic threshold adjustment mechanism. Twenty-two moderately skilled shooters completed three within-subject conditions (no-sound baseline, SMR enhancement, and theta suppression) in a single session with 32-channel EEG and behavioral data recorded simultaneously. Analyses employed whole-brain cluster-based permutation tests, cross-frequency coupling analysis, and functional connectivity analysis. Cluster-based permutation tests revealed that theta feedback induced a significant frontal 4-7 Hz suppression cluster (cluster

Indexed as

Heart RateNeurofeedbackBrainBrain-Computer InterfacesElectroencephalographyHumansMalebrain–computer interfacecross-frequency couplingdual-task interferencefrontal midline thetafunctional connectivityheartbeat sound feedbackindividual differencesneural mechanismsneurofeedback training

Identifiers

PMID42197993
PMCPMC13210765

What OpenQuestion holds

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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.