Affiliation:
1. School of Control Engineering Northeastern University Qinhuangdao Hebei 066001 China
2. Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Northeastern University at Qinhuangdao Qinhuangdao 066004 China
3. Department of Mechanical Engineering City University of Hong Kong Kowloon Tong Hong Kong SAR 999077 China
4. Department of Social and Behavioral Sciences City University of Hong Kong Kowloon Tong Hong Kong SAR 999077 China
5. Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong SAR 999077 China
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.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hebei Province
Fundamental Research Funds for the Central Universities
City University of Hong Kong