Wearable Internet of Things Gait Sensors for Quantitative Assessment of Myers–Briggs Type Indicator Personality

Yuliang Zhao; Hualin Xing; Xiaoai Wang; Yu Tian; Tingting Sun; Meng Chen; Dannii Y. L. Yeung; Samuel M. Y. Ho; Jianping Wang; Wen Jung Li

doi:10.1002/aisy.202300328

Wearable Internet of Things Gait Sensors for Quantitative Assessment of Myers–Briggs Type Indicator Personality

Yuliang Zhao, Hualin Xing, Xiaoai Wang, Yu Tian, Tingting Sun, Meng Chen^*, Dannii Y. L. Yeung, Samuel M. Y. Ho, Jianping Wang, Wen Jung Li^*

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

2 Citations (Scopus)

26 Downloads (CityUHK Scholars)

Abstract

Gait is a typical habitual human behavior and manifestation of personality. The unique properties of individual gaits may offer important clues in the assessment of personality. However, assessing personality accurately through quantitative gait analysis remains a daunting challenge. Herein, targeting young individuals, standardized gait data are obtained from 114 subjects with a wearable gait sensor, and the Myers–Briggs Type Indicator (MBTl) personality scale is used to assess their corresponding personality types. Artificial intelligence algorithms are used to systematically mine the relationship between gaits and 16 personality types. The work shows that gait parameters can indicate the personality of a subject from the four MBTI dimensions of E-l, S-N, T-F, and J-P with a concordance rate as high as 95%, 96%, 91%, and 91%, respectively. The overall measurement accuracy for the 16 personality types is 88.16%. Moreover, a personality tracking experiment on all the subjects after one year to assess the stability of their personality is also conducted. This research, which is based on a smart wearable Internet of Things gait sensor, not only establishes a new connection between behavioral analysis and personality assessment but also provides a set of accurate research tools for the quantitative assessment of personality. © 2023 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH.

Original language	English
Article number	2300328
Journal	Advanced Intelligent Systems
Volume	6
Issue number	3
Online published	19 Dec 2023
DOIs	https://doi.org/10.1002/aisy.202300328
Publication status	Published - Mar 2024

Funding

This work was supported by the National Natural Science Foundation of China (grant no. 61873307), Hebei Natural Science Foundation (grant nos. F2020501040, F2021203070, F2021501021), Fundamental Research Funds for the Central Universities (grant no. N2123004), the Administration of Central Funds Guiding the Local Science and Technology Development (grant no. 206Z1702G), the Hong Kong University Grants Council (GRF: #11210819, TRS: #T42-717/20-R, and CRF:# C7174-20G), and the City University of Hong Kong (SIRG: project No. 7020071).

Research Keywords

gaits
Myers–Briggs Type Indicator
personality
wearable sensors

Publisher's Copyright Statement

This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

Access Output

10.1002/aisy.202300328

221489811.pdfFinal Published version, 5.76 MBLicence: CC BY

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@article{833a6ad32eed4d84865bb7d285a11495,

title = "Wearable Internet of Things Gait Sensors for Quantitative Assessment of Myers–Briggs Type Indicator Personality",

abstract = "Gait is a typical habitual human behavior and manifestation of personality. The unique properties of individual gaits may offer important clues in the assessment of personality. However, assessing personality accurately through quantitative gait analysis remains a daunting challenge. Herein, targeting young individuals, standardized gait data are obtained from 114 subjects with a wearable gait sensor, and the Myers–Briggs Type Indicator (MBTl) personality scale is used to assess their corresponding personality types. Artificial intelligence algorithms are used to systematically mine the relationship between gaits and 16 personality types. The work shows that gait parameters can indicate the personality of a subject from the four MBTI dimensions of E-l, S-N, T-F, and J-P with a concordance rate as high as 95%, 96%, 91%, and 91%, respectively. The overall measurement accuracy for the 16 personality types is 88.16%. Moreover, a personality tracking experiment on all the subjects after one year to assess the stability of their personality is also conducted. This research, which is based on a smart wearable Internet of Things gait sensor, not only establishes a new connection between behavioral analysis and personality assessment but also provides a set of accurate research tools for the quantitative assessment of personality. {\textcopyright} 2023 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH.",

keywords = "gaits, Myers–Briggs Type Indicator, personality, wearable sensors",

author = "Yuliang Zhao and Hualin Xing and Xiaoai Wang and Yu Tian and Tingting Sun and Meng Chen and Yeung, {Dannii Y. L.} and Ho, {Samuel M. Y.} and Jianping Wang and Li, {Wen Jung}",

year = "2024",

month = mar,

doi = "10.1002/aisy.202300328",

language = "English",

volume = "6",

number = "3",

}

TY - JOUR

T1 - Wearable Internet of Things Gait Sensors for Quantitative Assessment of Myers–Briggs Type Indicator Personality

AU - Zhao, Yuliang

AU - Xing, Hualin

AU - Wang, Xiaoai

AU - Tian, Yu

AU - Sun, Tingting

AU - Chen, Meng

AU - Yeung, Dannii Y. L.

AU - Ho, Samuel M. Y.

AU - Wang, Jianping

AU - Li, Wen Jung

PY - 2024/3

Y1 - 2024/3

N2 - Gait is a typical habitual human behavior and manifestation of personality. The unique properties of individual gaits may offer important clues in the assessment of personality. However, assessing personality accurately through quantitative gait analysis remains a daunting challenge. Herein, targeting young individuals, standardized gait data are obtained from 114 subjects with a wearable gait sensor, and the Myers–Briggs Type Indicator (MBTl) personality scale is used to assess their corresponding personality types. Artificial intelligence algorithms are used to systematically mine the relationship between gaits and 16 personality types. The work shows that gait parameters can indicate the personality of a subject from the four MBTI dimensions of E-l, S-N, T-F, and J-P with a concordance rate as high as 95%, 96%, 91%, and 91%, respectively. The overall measurement accuracy for the 16 personality types is 88.16%. Moreover, a personality tracking experiment on all the subjects after one year to assess the stability of their personality is also conducted. This research, which is based on a smart wearable Internet of Things gait sensor, not only establishes a new connection between behavioral analysis and personality assessment but also provides a set of accurate research tools for the quantitative assessment of personality. © 2023 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH.

AB - Gait is a typical habitual human behavior and manifestation of personality. The unique properties of individual gaits may offer important clues in the assessment of personality. However, assessing personality accurately through quantitative gait analysis remains a daunting challenge. Herein, targeting young individuals, standardized gait data are obtained from 114 subjects with a wearable gait sensor, and the Myers–Briggs Type Indicator (MBTl) personality scale is used to assess their corresponding personality types. Artificial intelligence algorithms are used to systematically mine the relationship between gaits and 16 personality types. The work shows that gait parameters can indicate the personality of a subject from the four MBTI dimensions of E-l, S-N, T-F, and J-P with a concordance rate as high as 95%, 96%, 91%, and 91%, respectively. The overall measurement accuracy for the 16 personality types is 88.16%. Moreover, a personality tracking experiment on all the subjects after one year to assess the stability of their personality is also conducted. This research, which is based on a smart wearable Internet of Things gait sensor, not only establishes a new connection between behavioral analysis and personality assessment but also provides a set of accurate research tools for the quantitative assessment of personality. © 2023 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH.

KW - gaits

KW - Myers–Briggs Type Indicator

KW - personality

KW - wearable sensors

UR - http://www.scopus.com/inward/record.url?scp=85179982601&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85179982601&origin=recordpage

U2 - 10.1002/aisy.202300328

DO - 10.1002/aisy.202300328

M3 - RGC 21 - Publication in refereed journal

SN - 2640-4567

VL - 6

JO - Advanced Intelligent Systems

JF - Advanced Intelligent Systems

IS - 3

M1 - 2300328

ER -

Wearable Internet of Things Gait Sensors for Quantitative Assessment of Myers–Briggs Type Indicator Personality

Abstract

Funding

Research Keywords

Publisher's Copyright Statement

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

TBRS-ExtU-Lead: Intelligent Robotics for Elderly Assistance in Hong Kong

CRF-ExtU-Lead: Super Reality for Hands-on Online Education

GRF: Development of Flexible MEMS Pressure Sensors using Hierarchical Surface Structures for Texture Roughness Identification

Cite this

Wearable Internet of Things Gait Sensors for Quantitative Assessment of Myers–Briggs Type Indicator Personality

Abstract

Funding

Research Keywords

Publisher's Copyright Statement

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Projects

TBRS-ExtU-Lead: Intelligent Robotics for Elderly Assistance in Hong Kong

CRF-ExtU-Lead: Super Reality for Hands-on Online Education

GRF: Development of Flexible MEMS Pressure Sensors using Hierarchical Surface Structures for Texture Roughness Identification

Cite this