Possible insights into the respiration pacesetter mechanism derived from observations at acupuncture points
Description of this data
This data compliments a paper entitled: Possible insights into the respiration pacesetter mechanism derived from observations at acupuncture points. The paper fully describes and analyses the data.
At the time of writing, the paper is still in production. Please see the links at the end of this dataset, which will be updated once the paper is published.
Experiment data files
ex57 peaks etc .xlsx
The peak calculations. And also the sensor locations.
ex57 valuesIMP .xlsx
The impedance readings.
ex57 valuesTEMP .xlsx
The thermistor readings.
The Matlab script used to filter the readings and produce the plots.
Fig 01 .jpg
Impedance at left Lu-6.
Fig 02 .jpg
Impedance at left Lu-6, showing the duodenal and lung pace signals.
Fig 03 .jpg
Impedance at left ST-19, showing the exact correlation of the breathing pattern to the pace signal at left ST-19.
Fig 04 .jpg
Impedance at left ST-19, showing the increased amplitude of the duodenal pace signal while it was being used to set the respiration rate.
Impedance at left ST-19, showing the dropout due to the deep sighs.
Fig B ex57 st36 .jpg
Impedance at left ST-36, showing the lung pace signal superimposed upon this. See the peak values in the included "peak calculations" spreadsheet.
Steps to reproduce
The subject exercised by running on the spot for 3 minutes, which caused his respiration rate to increase. Then the real-time impedance at the following acupuncture points (acupoints) was monitored while he sat relaxed as his respiration rate slowed: left Lung-6 (Kongzui), Lung-9 (Taiyuan), Stomach-19 (Burong), Stomach-36 (Zusanli), and bilateral Kidney-3 (Taixi). A thermistor was also placed under his nose to record his breathing cycle.
The acupoints were first located by an acupuncturist with 13 years experience in Chinese acupuncture, then the location of lowest impedance was verified electrically, and this was used as the test location.
At each acupoint, a pair of custom-made electrodes were used, set at a distance of 6 mm apart (the second acting as a control), and a standard ECG electrode was attached at about 5 cm from each acupoint, as an earth. Gel was used on each electrode. A 40 kHz 200 mv sine wave was passed through the electrodes, and the voltage monitored. A custom-made unit converted the monitored voltages to DC, then passed these to a data logger which sampled the voltages at 1 kHz. The thermistor was attached to a simple voltage divider circuit and a direct current passed through it. The voltage across the thermistor was monitored by another data logger, also sampling at 1 kHz. An Access database and macro was used to control the data loggers and convert the voltage samples into kΩ and Celsius values, before they were imported into Matlab and filtered to produce the plots.
Full details of all the techniques and equipment used (including how to reliably locate acupoints electrically) can be found in the following documents.
The subject was a male, aged 34. In Chinese medicine terms, he suffered poor stomach and pancreas function (usually known as “Stomach chi deficiency” and “Spleen chi deficiency”); and also poor “kidney” function (known as “Kidney chi deficiency”).
The subject had not eaten a large meal since the previous evening. The recording began at 13:04 on 9 November 2018 and lasted for 600 s (10 mins). At 458 s, he held his breath for 17 s. He pressed a footswitch to indicate the start and end of holding his breath. This produced 2 time values, which are marked on the plots with vertical green lines.
He sighed at the following times (length of sigh in brackets), which are visible on the thermistor plot of Figure 1: 133.7 (4.1 s), 203.2 (10.7 s), 284.4 (9.8 s), 425.6 (7.6 s).
After the recording, it was noted that the following electrodes had moved from their marked position, which probably happened during the initial running on the spot: left Kidney-3 (by 4mm distal), left Lung-9 (by 2mm proximal), and left Stomach-19 (by 3mm caudal).
Informed consent was obtained.
Cite this dataset
Kovich, Fletcher (2019), “Possible insights into the respiration pacesetter mechanism derived from observations at acupuncture points”, Mendeley Data, v1 http://dx.doi.org/10.17632/bh8xmpfs48.1
The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.