CHARACTERIZATION OF DICHOTOMOUS EMOTIONAL STATES USING ELECTRODERMAL ACTIVITY BASED GEOMETRIC FEATURES

被引：0

作者：

Veeranki Y.R. ^{[1
]}

Ganapathy N. ^{[1
,2
]}

Swaminathan R. ^{[1
]}

机构：

[1] Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Tamil Nadu, Chennai

[2] Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Braunschweig

来源：

Biomedical Sciences Instrumentation | 2022年 / 58卷 / 02期

关键词：

Classification; Electrodermal activity; Emotion; Geometric features;

D O I：

10.34107/NSJX733575

中图分类号：

学科分类号：

摘要：

In this work, an attempt has been made to classify dichotomous emotional states using Electrodermal activity (EDA) and geometric features. For this, the annotated happy and sad EDA is obtained from the online public database. The EDA is subjected to discrete Fourier transform, and Fourier coefficients in the complex plane are obtained. The envelope of the complex plane is identified using the α-shape method. Five geometric features, namely center of gravity, eccentricity, convexity, rectangularity, and convex hull area are computed from the envelope and statistical analysis is performed. Two machinelearning algorithms, namely random forest (RF) and support vector machine, are considered for the classification. The results show that the proposed approach is able to classify the dichotomous emotional states. The rectangularity feature is found to be distinct and shows a statistically significant difference between the happy and sad emotional states (p<0.05). The RF classifier yields the highest F-m and AUC of 87.8% and 93.8%, respectively in differentiating emotional states. Thus, it appears that the proposed method could be used to understand the neurological, psychiatric, and biobehavioral mechanisms associated with happy and sad emotional states. © 2022 IAE All rights reserved.

引用

页码：75 / 81

页数：6

共 12 条

[1]

Kleinginna P.R., Kleinginna A.M., A categorized list of emotion definitions, with suggestions for a consensual definition, Motiv. Emot., 5, 4, pp. 345-379, (1981)

[2]

Ekman P., An argument for basic emotions, Cogn. Emot., 6, 34, pp. 169-200, (1992)

[3]

An S., Ji L.-J., Marks M., Zhang Z., Two Sides of Emotion: Exploring Positivity and Negativity in Six Basic Emotions across Cultures, Front. Psychol., 8, (2017)

[4]

Cohn M.A., Fredrickson B.L., Brown S.L., Mikels J.A., Conway A.M., Happiness Unpacked: Positive Emotions Increase Life Satisfaction by Building Resilience, Emot. Wash. DC, 9, 3, pp. 361-368, (2009)

[5]

Burgdorf J., Panksepp J., The neurobiology of positive emotions, Neurosci. Biobehav. Rev., 30, 2, pp. 173-187, (2006)

[6]

Lyubomirsky S., King L., Diener E., The Benefits of Frequent Positive Affect: Does Happiness Lead to Success?, Social Science Research Network, Rochester, NY, SSRN Scholarly Paper ID 2199192, (2013)

[7]

Arias J.A., Et al., The neuroscience of sadness: A multidisciplinary synthesis and collaborative review, Neurosci. Biobehav. Rev., 111, pp. 199-228, (2020)

[8]

Vanlessen N., De Raedt R., Koster E.H.W., Pourtois G., Happy heart, smiling eyes: A systematic review of positive mood effects on broadening of visuospatial attention, Neurosci. Biobehav. Rev., 68, pp. 816-837, (2016)

[9]

Ho C.-C., Macdorman K.F., Pramono Z.A.D.D., Human emotion and the uncanny valley: A GLM, MDS, and Isomap analysis of robot video ratings, Proceedings of the 3Rd ACM/IEEE International Conference on Human Robot Interaction, pp. 169-176, (2008)

[10]

Millgram Y., Joormann J., Huppert J.D., Lampert A., Tamir M., Motivations to Experience Happiness or Sadness in Depression: Temporal Stability and Implications for Coping With Stress:, Clin. Psychol. Sci., (2018)

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