Automatic Personality Assessment through Movement Analysis

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Show simple item record Delgado Gómez, David Masó Besga, Antonio Eduardo Aguado, David Rubio, Víctor J. Sujar, Aaron Bayona, Sofia 2022-06-06T08:27:36Z 2022-06-06T08:27:36Z 2022-05-01
dc.identifier.bibliographicCitation Delgado-Gómez, D., Masó-Besga, A. E., Aguado, D., Rubio, V. J., Sujar, A., & Bayona, S. (2022). Automatic Personality Assessment through Movement Analysis. In Sensors, 22,(10), p. 3949-3960
dc.identifier.issn 1424-3210
dc.description.abstract Obtaining accurate and objective assessments of an individual’s personality is vital in many areas including education, medicine, sports and management. Currently, most personality assessments are conducted using scales and questionnaires. Unfortunately, it has been observed that both scales and questionnaires present various drawbacks. Their limitations include the lack of veracity in the answers, limitations in the number of times they can be administered, or cultural biases. To solve these problems, several articles have been published in recent years proposing the use of movements that participants make during their evaluation as personality predictors. In this work, a multiple linear regression model was developed to assess the examinee’s personality based on their movements. Movements were captured with the low-cost Microsoft Kinect camera, which facilitates its acceptance and implementation. To evaluate the performance of the proposed system, a pilot study was conducted aimed at assessing the personality traits defined by the Big-Five Personality Model. It was observed that the traits that best fit the model are Extroversion and Conscientiousness. In addition, several patterns that characterize the five personality traits were identified. These results show that it is feasible to assess an individual’s personality through his or her movements and open up pathways for several research.
dc.description.sponsorship This research was partially funded by the Spanish National Project, grant number RTI2018- 101857-B-I00. Additionally, by Instituto Salud Carlos III, grant number DTS21/00091. It has been also partially supported by Ministerio de Ciencia e Innovación PID2020-114911GB-I00.
dc.format.extent 11
dc.language.iso eng
dc.publisher MDPI AG
dc.rights © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
dc.rights Atribución 3.0 España
dc.subject.other Personality Assessment
dc.subject.other Movement
dc.subject.other Kinect
dc.subject.other Big-Five Model
dc.title Automatic Personality Assessment through Movement Analysis
dc.type article
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. RTI2018-101857-B-I00
dc.relation.projectID Gobierno de España. DTS21/00091
dc.relation.projectID Gobierno de España. PID2020-114911GB-I00
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 3949
dc.identifier.publicationissue 10
dc.identifier.publicationlastpage 3960
dc.identifier.publicationtitle Sensors
dc.identifier.publicationvolume 20
dc.identifier.uxxi AR/0000030653
dc.contributor.funder Ministerio de Ciencia e Innovación (España)
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