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      Detecting Happiness Using Hyperspectral Imaging Technology

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          Abstract

          Hyperspectral imaging (HSI) technology can be used to detect human emotions based on the power of material discrimination from their faces. In this paper, HSI is used to remotely sense and distinguish blood chromophores in facial tissues and acquire an evaluation indicator (tissue oxygen saturation, StO 2) using an optical absorption model. This study explored facial analysis while people were showing spontaneous expressions of happiness during social interaction. Happiness, as a psychological emotion, has been shown to be strongly linked to other activities such as physiological reaction and facial expression. Moreover, facial expression as a communicative motor behavior likely arises from musculoskeletal anatomy, neuromuscular activity, and individual personality. This paper quantified the neuromotor movements of tissues surrounding some regions of interest (ROIs) on smiling happily. Next, we selected six regions—the forehead, eye, nose, cheek, mouth, and chin—according to a facial action coding system (FACS). Nineteen segments were subsequently partitioned from the above ROIs. The affective data (StO 2) of 23 young adults were acquired by HSI while the participants expressed emotions (calm or happy), and these were used to compare the significant differences in the variations of StO 2 between the different ROIs through repeated measures analysis of variance. Results demonstrate that happiness causes different distributions in the variations of StO 2 for the above ROIs; these are explained in depth in the article. This study establishes that facial tissue oxygen saturation is a valid and reliable physiological indicator of happiness and merits further research.

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          Most cited references63

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          Autonomic nervous system activity in emotion: A review

          Autonomic nervous system (ANS) activity is viewed as a major component of the emotion response in many recent theories of emotion. Positions on the degree of specificity of ANS activation in emotion, however, greatly diverge, ranging from undifferentiated arousal, over acknowledgment of strong response idiosyncrasies, to highly specific predictions of autonomic response patterns for certain emotions. A review of 134 publications that report experimental investigations of emotional effects on peripheral physiological responding in healthy individuals suggests considerable ANS response specificity in emotion when considering subtypes of distinct emotions. The importance of sound terminology of investigated affective states as well as of choice of physiological measures in assessing ANS reactivity is discussed. Copyright © 2010 Elsevier B.V. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Comput Intell Neurosci
                Comput Intell Neurosci
                CIN
                Computational Intelligence and Neuroscience
                Hindawi
                1687-5265
                1687-5273
                2019
                15 January 2019
                : 2019
                : 1965789
                Affiliations
                1School of Electronic and Information Engineering, Southwest University, Chongqing, China
                2Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing, Southwest University, Chongqing, China
                3Illinois State University, Normal, IL, USA
                4Center of Technical Support for Network Security, Chongqing Municipal Public Security Bureau, Chongqing, China
                5College of Computer and Information Science, Southwest University, Chongqing, China
                Author notes

                Academic Editor: Laura Marzetti

                Author information
                http://orcid.org/0000-0001-5696-7745
                http://orcid.org/0000-0002-8058-5947
                Article
                10.1155/2019/1965789
                6350538
                49f25e38-f977-40cf-bb4e-722c97ab1c6d
                Copyright © 2019 Min Hao et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 August 2018
                : 22 November 2018
                : 3 December 2018
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 61872301
                Funded by: Chongqing Key Laboratory of Non-linear Circuit and Intelligent Information Processing
                Categories
                Research Article

                Neurosciences
                Neurosciences

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