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[Discussion on the closed-loop regulation strategy for acupuncture "Deqi" based on brain-computer interface and its peripheral-central mechanisms].

Created on 23 Oct 2026

Authors

Ling Yin, Yong Ye, Yuxiang Li, Jing Luo, Hui Zhou, Yuelun Tian, Rong Luo

Published in

Zhen ci yan jiu = Acupuncture research. Volume 51. Issue 10. Pages 1354-1366. Oct 25, 2026.

Abstract

It is held that "Deqi" is the key to the therapeutic effect of acupuncture, but its evaluation has long relied on subjective feelings and lacks objective biological indicators. In the present article, we systematically review the current research status of brain-computer interface (BCI) technology based on electroencephalogram (EEG) in analyzing the peripheral-cerebral neural mechanism of "Deqi", and further explore how to utilize the closed-loop regulation ability of BCI to actively induce and maintain the "Deqi" state. By integrating domestic and foreign literature, we analyzed the peripheral initiation mechanism and central response characteristics of "Deqi", and explored its application value of EEG-BCI in the objective identification and the construction of closed-loop feedback systems. Studies have demonstrated that EEG, with its millisecond-level time resolution, can capture the dynamic changes of neural oscillations during the "Deqi" process in real time. The feature decoding method based on machine learning further realizes the objective identification of the "Deqi" state, while the closed-loop feedback system constructed by BCI technology provides an innovative path for precise acupuncture treatment. However, this field still faces some challenges such as signal artifact interference, insufficient decoding accuracy, and inconsistent research paradigms. The deep integration of EEG-BCI with acupuncture medicine provides a key technical platform for decoding the scientific connotation of "Deqi" and active regulation. In the future, efforts should be made to develop dynamic network decoding technology, further deepen the research on peripheral-cerebral coupling mechanisms, and promote the transformation of the system towards intelligence and standardization.

PMID:
42908451
Bibliographic data and abstract were imported from PubMed on 23 Oct 2026.

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