Real-time samples of impedances at ST-36, GB-34, and a NAP
Description of this data
The impedances at right and left ST-36, GB-34 and a non-acupoint (NAP) were sampled at the rate of 1KHz for 5 minutes while the subject sat in a chair, relaxed. The included charts show the results, which are analysed in detail in a paper (“The electrical anatomy of acupuncture points”) which is currently in preparation.
Experiment data files
ex33a Ch1_15 .xlsx
The data for all channels.
The samples used to plot the "cross section" of GB-34.
The Matlab script used to filter the data and produce the plots.
Fig01 ex33a rGB34 p6 .png
Plot of impedance at right GB-34 and at 6mm radius, showing features reflecting gallbladder activity.
Plot of "cross section" of the impedance pattern at GB34.
Plot of impedance at right ST36 and 6mm radius.
Plot of impedance at right and left GB34.
Plot of the impedances at left GB34 and 6mm radius, with insets showing closeups of the two main features.
Steps to reproduce
The session began at 10:34am on 29 March 2018.
The subject was a male, aged 58, with poor stomach and pancreas function, who was sat in a chair relaxed. The acupoints were first located by and experienced TCM practitioner, then the locations of lowest impedance verified electrically. For each acupoint, the impedance was measured at the centre, and also at 6mm radius.
The signal used was a 200mv sine wave at 40 KHz. This was passed into the electrodes and the resultant voltages monitored at a sampling rate of 1KHz for 5 minutes. The samples were recorded by a data logger, then imported into Matlab and filtered to produce the plots included here. The data logger was controlled by a VBA macro in an Access database, which also stored the samples.
For detailed descriptions of the equipment and techniques used, please see the following pdf documents.
Cite this dataset
Kovich, Fletcher (2018), “Real-time samples of impedances at ST-36, GB-34, and a NAP”, Mendeley Data, v1 http://dx.doi.org/10.17632/fwfysz9x52.1
The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.