Assessment of Human Personality Traits Using Smartphone Sensing

Assessing human personality through gait patterns is one of the newest and most widespread research areas. Gait refers to an individual’s walking style that represents a person’s identity and can reflect reliable information about mood, emotion, and intrinsic personality traits under scrutiny. Based on data, it focuses on deriving key personality traits of individuals along the Big Five model of personality. This research collects a new dataset of 22 participants using smartphones for experimentation according to the user’s Big-Five Personality Traits Profiles (BFPT). The Random Forest classifier is applied to train and classify the dataset. Experimental results and performance evaluations of the classifier demonstrate the effectiveness of the proposed scheme for all Big Five Personality Traits.