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

Saved in:
Bibliographic Details
Title: Working Memory Capacity for Mid-Air Gestures in Human–Computer Interaction.
Authors: Zhou, Xiaozhou (AUTHOR), Lu, Zhengyang (AUTHOR), Bai, Ruidong (AUTHOR), Wang, Yixue (AUTHOR), Zhang, Ziwei (AUTHOR), Qiu, Xu-Yi (AUTHOR)
Source: International Journal of Human-Computer Interaction. Jul2025, Vol. 41 Issue 14, p8565-8580. 16p.
Subjects: Human-computer interaction, Gesture, Interactive computer systems, Empirical research, Short-term memory, Memory span, Cognitive load
Abstract: 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. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 186603323
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Working Memory Capacity for Mid-Air Gestures in Human–Computer Interaction.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Zhou%2C+Xiaozhou%22">Zhou, Xiaozhou</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lu%2C+Zhengyang%22">Lu, Zhengyang</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bai%2C+Ruidong%22">Bai, Ruidong</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Yixue%22">Wang, Yixue</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Ziwei%22">Zhang, Ziwei</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qiu%2C+Xu-Yi%22">Qiu, Xu-Yi</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Jul2025, Vol. 41 Issue 14, p8565-8580. 16p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Human-computer+interaction%22">Human-computer interaction</searchLink><br /><searchLink fieldCode="DE" term="%22Gesture%22">Gesture</searchLink><br /><searchLink fieldCode="DE" term="%22Interactive+computer+systems%22">Interactive computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Empirical+research%22">Empirical research</searchLink><br /><searchLink fieldCode="DE" term="%22Short-term+memory%22">Short-term memory</searchLink><br /><searchLink fieldCode="DE" term="%22Memory+span%22">Memory span</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+load%22">Cognitive load</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=186603323
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/10447318.2024.2411469
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 8565
    Subjects:
      – SubjectFull: Human-computer interaction
        Type: general
      – SubjectFull: Gesture
        Type: general
      – SubjectFull: Interactive computer systems
        Type: general
      – SubjectFull: Empirical research
        Type: general
      – SubjectFull: Short-term memory
        Type: general
      – SubjectFull: Memory span
        Type: general
      – SubjectFull: Cognitive load
        Type: general
    Titles:
      – TitleFull: Working Memory Capacity for Mid-Air Gestures in Human–Computer Interaction.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Zhou, Xiaozhou
      – PersonEntity:
          Name:
            NameFull: Lu, Zhengyang
      – PersonEntity:
          Name:
            NameFull: Bai, Ruidong
      – PersonEntity:
          Name:
            NameFull: Wang, Yixue
      – PersonEntity:
          Name:
            NameFull: Zhang, Ziwei
      – PersonEntity:
          Name:
            NameFull: Qiu, Xu-Yi
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 10447318
          Numbering:
            – Type: volume
              Value: 41
            – Type: issue
              Value: 14
          Titles:
            – TitleFull: International Journal of Human-Computer Interaction
              Type: main
ResultId 1