Volume 12 Supplement 1

Scientific Abstracts Presented at the International Research Congress on Integrative Medicine and Health 2012

Open Access

P02.178. Skin conductance at 24 Source (Yuan) acupoints in 8637 patients: influence of age, gender and time of day

  • S Chamberlin1,
  • A Colbert1 and
  • A Larsen2
BMC Complementary and Alternative MedicineThe official journal of the International Society for Complementary Medicine Research (ISCMR)201212(Suppl 1):P234

https://doi.org/10.1186/1472-6882-12-S1-P234

Published: 12 June 2012

Purpose

The clinical practice of recording skin conductance (SC) at acupuncture points (acupoints), as a diagnostic and/or therapeutic monitoring aid may have scientific merit. However, influences of age, gender and time of day on these recordings are unknown and it is unclear whether SC at acupoints differs from SC levels in general (as reported in psychophysiology research). This research will investigate these influences.

Methods

This analysis summarizes SC data obtained with the AcuGraph 3 Digital Meridian Imaging System between June 2005 and March 31, 2010. An initial dataset of 117,725 SC examinations was scrubbed to include only the first SC examination on individual patients and exclude potentially faulty data. The final dataset consists of SC recordings at the 24 Source (Yuan) acupoints in 8637 patients, collected by 311 practitioners. Twelve left/right average conductance measures and an overall average of the 24 acupoints were assessed. Statistical analyses included two sample t tests, three way analyses of variance and linear regression.

Results

Results indicate that mean SC at acupoints, similar to SC in general, is higher in males, higher in afternoons and declines with age. Not previously reported, the rate of SC decline with age differs at different acupoints between males and females.

Conclusion

These findings have substantial implications for acupuncture research and practice. Patterns derived from measures such as these should be investigated as potential early detectors of disease and predictors of treatment responsiveness.

Authors’ Affiliations

(1)
National College of Natural Medicine, Helfgott Research Institute
(2)
Meridia Technologies, Inc.

Copyright

© Chamberlin et al; licensee BioMed Central Ltd. 2012

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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