Automatic Personality Assessment through Movement Analysis
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 que...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/10/3949 |
| _version_ | 1797495578603552768 |
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| author | David Delgado-Gómez Antonio Eduardo Masó-Besga David Aguado Victor J. Rubio Aaron Sujar Sofia Bayona |
| author_facet | David Delgado-Gómez Antonio Eduardo Masó-Besga David Aguado Victor J. Rubio Aaron Sujar Sofia Bayona |
| author_sort | David Delgado-Gómez |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T01:51:38Z |
| format | Article |
| id | doaj.art-11da4fe4c0754410b336453bdff3fc07 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T01:51:38Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-11da4fe4c0754410b336453bdff3fc072023-11-23T13:04:01ZengMDPI AGSensors1424-82202022-05-012210394910.3390/s22103949Automatic Personality Assessment through Movement AnalysisDavid Delgado-Gómez0Antonio Eduardo Masó-Besga1David Aguado2Victor J. Rubio3Aaron Sujar4Sofia Bayona5Department of Statistics, Universidad Carlos III, 28903 Getafe, SpainUNED, Universidad Nacional de Educación a Distancia, 28015 Madrid, SpainDepartment of Social Psychology and Methodology, Autónoma University of Madrid, 28049 Madrid, SpainDepartment of Biological and Health Psychology, Autónoma University of Madrid, 28049 Madrid, SpainDepartment of Computer Engineering, Universidad Rey Juan Carlos, 28933 Madrid, SpainDepartment of Computer Engineering, Universidad Rey Juan Carlos, 28933 Madrid, SpainObtaining 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.https://www.mdpi.com/1424-8220/22/10/3949personality assessmentmovementKinectBig-Five model |
| spellingShingle | David Delgado-Gómez Antonio Eduardo Masó-Besga David Aguado Victor J. Rubio Aaron Sujar Sofia Bayona Automatic Personality Assessment through Movement Analysis Sensors personality assessment movement Kinect Big-Five model |
| title | Automatic Personality Assessment through Movement Analysis |
| title_full | Automatic Personality Assessment through Movement Analysis |
| title_fullStr | Automatic Personality Assessment through Movement Analysis |
| title_full_unstemmed | Automatic Personality Assessment through Movement Analysis |
| title_short | Automatic Personality Assessment through Movement Analysis |
| title_sort | automatic personality assessment through movement analysis |
| topic | personality assessment movement Kinect Big-Five model |
| url | https://www.mdpi.com/1424-8220/22/10/3949 |
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