Working Memory Capacity for Mid-Air Gestures in Human–Computer Interaction

手势 人机交互 计算机科学 沟通 认知心理学 心理学 人工智能
作者
Xiaozhou Zhou,Zhengyang Lu,Ruidong Bai,Yixue Wang,Ziwei Zhang,Xuyi Qiu
出处
期刊:International Journal of Human-computer Interaction [Taylor & Francis]
卷期号:: 1-16
标识
DOI:10.1080/10447318.2024.2411469
摘要

Mid-air gesture interactions have emerged as one of the predominant modalities used in human-computer interaction (HCI). However, extant research on gestures predominantly concentrates on the design of gestures for singular functionalities, which requires a comprehensive investigation into gesture interaction design from an integrative HCI system perspective. Working memory capacity plays a pivotal role in constraining the number of gestures accommodated within an HCI system. This study adopts the change detection paradigm to conduct an empirical investigation into the working memory capacities associated with mid-air gestures, aiming to elucidate the working memory capacity for such gestures. The experimental design included two independent variables: five distinct categories of mid-air gestures (physical, symbolic, metaphorical, abstract, and mixed) and memory set sizes ranging from two to nine items. The findings revealed that working memory capacities for different types of gestures fluctuate between three and five items, with symbolic gestures presenting the most negligible cognitive load for recall and abstract gestures proving to be the most challenging. The outcomes of this research have significant implications for both the design of individual gestures and the overarching design of gesture interaction systems, serving as a valuable reference for future endeavors in HCI design optimization.

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