Literature DB >> 23322071

Electrodermal activity at acupuncture points differentiates patients with current pain from pain-free controls.

Linda Turner1, Wolfgang Linden, Candace Marshall.   

Abstract

This study evaluated whether electrodermal resistance at acupuncture points (AP) systematically varies as a function of pain. The study was conceived as a proof-of-principle study in support of research on acupuncture and other complementary medicine approaches. Specifically, this study investigates whether or not electrodermal activity systematically differentiates arthritis patients with current pain from pain-free controls. Participants with rheumatoid arthritis (n = 32) and a typical pain level of at least 3 (on a 0-10 scale) were compared with case controls (n = 28) who had no medical diagnosis and were pain free. Electrodermal resistance at AP was measured with a commercial ohmmeter and compared to heart rate, blood pressure, and ratings on the Pain Catastrophization Scale and the McGill Melzack Pain Questionnaire. There were consistent differences between the experimental group and the control group on all markers of pain. Similarly, there were significant group differences and some trends for electrodermal activity at the AP labeled 'bladder,' 'gall bladder,' and 'small intestine.' It is concluded that the concept of electrodermal resistance at AP possesses criterion validity for distinguishing pain from a no pain state. This research provides support for the usefulness of measuring electrodermal activity when testing energy-based models of disease, and can be seen as a bridge between Western and Chinese medicine.

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Year:  2013        PMID: 23322071     DOI: 10.1007/s10484-013-9209-6

Source DB:  PubMed          Journal:  Appl Psychophysiol Biofeedback        ISSN: 1090-0586


  2 in total

1.  Using electrodermal activity to validate multilevel pain stimulation in healthy volunteers evoked by thermal grills.

Authors:  Hugo F Posada-Quintero; Youngsun Kong; Kimberly Nguyen; Cara Tran; Luke Beardslee; Longtu Chen; Tiantian Guo; Xiaomei Cong; Bin Feng; Ki H Chon
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2020-07-29       Impact factor: 3.619

2.  Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity.

Authors:  Hugo F Posada-Quintero; Youngsun Kong; Ki H Chon
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2021-06-16       Impact factor: 3.210

  2 in total

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