Quantification EEG under manual acupuncture stimulation of different manipulation in Qu Chi acupoint

Quan Cheng; Han Yu; Hongxue Zuo

doi:10.1117/12.2636701

10 June 2022 Quantification EEG under manual acupuncture stimulation of different manipulation in Qu Chi acupoint

Quan Cheng, Han Yu, Hongxue Zuo

Proceedings Volume 12179, Second International Conference on Medical Imaging and Additive Manufacturing (ICMIAM 2022); 121791A (2022) https://doi.org/10.1117/12.2636701
Event: Second International Conference on Medical Imaging and Additive Manufacturing (ICMIAM 2022), 2022, Xiamen, China

Abstract

Acupuncture is a critical part of Chinese Traditional medicine, and its efficacy has been proved by long-term clinical practice. However, the function effect on the neural system and mechanism of acupuncture manipulation (MA) is still unclear. The paper explores the mechanism of lifting-thrusting manipulations of acupuncture from an electroencephalogram (EEG) perspective. An experiment is implemented that acupuncture at Quchi point (LI11) is stimulated with two different manipulations (reinforcing and reducing manipulation), and EEG was collected during the stimulation. Then EEG features of brain rhythm are calculated to analyze the response of different acupuncture manipulation before and after stimulation. The research shows that compared with the pre-acupuncture period to the post-acupuncture period, the energy of the EEG signal decreased in the theta rhythm and increased in beta rhythm. Overall, this paper provides an insight into the quantification of brain electrical activity response of acupuncture manipulation in Qu Chi acupoint. The research results could present a quantitative study method for the neural response of MA stimulation．

Citation Download Citation

Quan Cheng, Han Yu, and Hongxue Zuo "Quantification EEG under manual acupuncture stimulation of different manipulation in Qu Chi acupoint", Proc. SPIE 12179, Second International Conference on Medical Imaging and Additive Manufacturing (ICMIAM 2022), 121791A (10 June 2022); https://doi.org/10.1117/12.2636701

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KEYWORDS

Electroencephalography

Brain

Surgery

Head

Medicine

Statistical analysis

Analytical research

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