Luminescence of Acupuncture Point in Darkened Area under Optical Pulse Excitation of Adjoining Areas of Investigated Meridian

Navrotskv, Leonid G.; Lisitsyna, L.I.; Блохин, А. П.; Kamardin, Alexander. E.; Belavskaya, S.V.; Poteryaeva, E. L.

doi:10.1109/edm.2018.8435042

Cited by 2 publications

(2 citation statements)

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“…In recent years, Traditional Chinese Medicine (TCM) has been gaining more and more attention as the traditional therapy of complementary and alternative medicine (CAM) in the world due to its simplicity, convenience, efficiency, and cheapness [1][2][3]. ere is a growing amount of studies on specificities of meridian acupoints through biophysics [4][5][6], electrophysiology [7][8][9], infrared imaging [3,10], and so forth.…”

Section: Introductionmentioning

confidence: 99%

“…However, up to now, there are few researches on the modeling of meridian system from the perspective of electronic information transmission. In addition, these studies mainly explored the hysteresis characteristics of meridian system through electronic acupoint stimulation signals [15] rather than directly exploring through acupoint electric potential signals [8,10]. In some papers, the characteristics of parts of the body's meridians were studied [16][17][18], but rarely from the holistic theory of Chinese medicine, the systematic study of the twelve meridians was done in a human body.…”

Section: Introductionmentioning

confidence: 99%

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Study on Potential of Meridian Acupoints of Traditional Chinese Medicine

Zhao

Wang

et al. 2021

Journal of Healthcare Engineering

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In recent years, Traditional Chinese Medicine (TCM) has attracted more and more attention due to its good therapeutic effect, low cost, and convenience. This research is also a part of the goal of the modernization of TCM. Based on the meridian electric potential acquisition system independently developed by our project team, in this paper, we designed the human body's meridian electric potential acquisition scheme. We use principal component analysis (PCA) to prove that the meridional potential signal is derived from the ECG signal. Then, Inception ResNet V2 was used to classify acupoints and nonacupoints. Finally, the classification accuracy rate reached 86.59045265, and the F1 score = 0.72161642. This shows that acupoints and nonacupoints can be distinguished by their surface potential.

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