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自主和非自主皮肤电活动的心肺分类器。

A cardiorespiratory classifier of voluntary and involuntary electrodermal activity.

机构信息

Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.

出版信息

Biomed Eng Online. 2010 Feb 25;9:11. doi: 10.1186/1475-925X-9-11.

DOI:10.1186/1475-925X-9-11
PMID:20184746
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2851698/
Abstract

BACKGROUND

Electrodermal reactions (EDRs) can be attributed to many origins, including spontaneous fluctuations of electrodermal activity (EDA) and stimuli such as deep inspirations, voluntary mental activity and startling events. In fields that use EDA as a measure of psychophysiological state, the fact that EDRs may be elicited from many different stimuli is often ignored. This study attempts to classify observed EDRs as voluntary (i.e., generated from intentional respiratory or mental activity) or involuntary (i.e., generated from startling events or spontaneous electrodermal fluctuations).

METHODS

Eight able-bodied participants were subjected to conditions that would cause a change in EDA: music imagery, startling noises, and deep inspirations. A user-centered cardiorespiratory classifier consisting of 1) an EDR detector, 2) a respiratory filter and 3) a cardiorespiratory filter was developed to automatically detect a participant's EDRs and to classify the origin of their stimulation as voluntary or involuntary.

RESULTS

Detected EDRs were classified with a positive predictive value of 78%, a negative predictive value of 81% and an overall accuracy of 78%. Without the classifier, EDRs could only be correctly attributed as voluntary or involuntary with an accuracy of 50%.

CONCLUSIONS

The proposed classifier may enable investigators to form more accurate interpretations of electrodermal activity as a measure of an individual's psychophysiological state.

摘要

背景

皮肤电反应(EDR)可归因于许多来源,包括皮肤电活动(EDA)的自发波动以及深呼吸、自愿的心理活动和惊跳事件等刺激。在使用 EDA 作为心理生理状态测量的领域中,EDR 可能由许多不同的刺激引起这一事实经常被忽略。本研究试图将观察到的 EDR 分为自愿(即由有意的呼吸或心理活动产生)或非自愿(即由惊跳事件或自发的皮肤电波动产生)。

方法

八名身体健康的参与者接受了可能导致 EDA 变化的条件:音乐想象、惊跳噪声和深呼吸。开发了一个以用户为中心的心肺分类器,包括 1)EDR 检测器、2)呼吸过滤器和 3)心肺过滤器,用于自动检测参与者的 EDR,并将其刺激的来源分类为自愿或非自愿。

结果

检测到的 EDR 的阳性预测值为 78%,阴性预测值为 81%,总体准确性为 78%。没有分类器,EDR 只能以 50%的准确性正确归因于自愿或非自愿。

结论

所提出的分类器可以使研究人员能够更准确地将皮肤电活动解释为个体心理生理状态的测量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/4655ad709ff8/1475-925X-9-11-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/cfdf58d9294d/1475-925X-9-11-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/65aa3fb392f9/1475-925X-9-11-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/828b0478915e/1475-925X-9-11-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/4655ad709ff8/1475-925X-9-11-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/cfdf58d9294d/1475-925X-9-11-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/65aa3fb392f9/1475-925X-9-11-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/828b0478915e/1475-925X-9-11-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9192/2851698/4655ad709ff8/1475-925X-9-11-4.jpg

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