Analysis of users’ semantic network model for gesture interaction

Abstract

Recently, gesture interaction has been rapidly adopted for consumer produdcts to implement Natural User Interaction. This study focused on analysis of users’ perception on gesture interaction, which could be categorized as follows: semaphoric gesture interaction and manipulative gesture interaction. Contents analysis and semantic network analysis were conducted to contrast existing UX issues in the two gesture interactions. From the contents analysis on user reviews, it is found that semaphoric gesture interation intrigued more usability issues than manipulative gesture interaction, and the issues emphasized efficiency and accuracy rather than fun and flexibility. From the semantic network analysis, it is found that fun and physical fatigue were the most distinguished among 121 keywords used in users’ descriptions of semaphoric gesture interaction while accuracy and familiarity were relatively important for manipulative gesture interaction. Also, it is observed that having hands-on experiences changed the structures of users’ semantic network for both gesture interactions. Based on the content analysis and semantic network analysis, the following six UX issues are identified: limited by hardware, intuitive interaction, familiarity effect, eye-motor coordination, fatigue in repetition, and integrity in interaction.