Embodied Embroidery: Somaesthetic Interaction Design for Women's Masturbation

Dianya Mia Hua, Jeffrey Bardzell, Shaowen Bardzell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Though a taboo topic, women's masturbation is the most effective technique in producing orgasms among all sexual behaviors [37]. This project explores how somaesthetic interaction design can contribute to designing for women's sexual pleasure, challenging androcentric discourses on women's sexuality, and also the desexualization of women with dis/abilities. In the study, the first author, who identifies as a woman with an invisible disability, experiments with other women's masturbatory techniques using her own body as a design resource. She then articulated that intersubjective engagement using her own body as an artistic medium in the form of Embodied Embroidery, a practice inspired by women's artmaking, and which seeks to foreground the aesthetic dimensions of experiential knowledge to support theory-making in design. Guided by three key features of somaesthetic interaction - first-person perspective, intersubjectivity, and articulation - this pictorial contributes to pleasure activism in the domain of HCI and interaction design.

Original languageEnglish (US)
Title of host publicationTEI 2023 - Proceedings of the 17th International Conference on Tangible, Embedded, and Embodied Interaction
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450399777
DOIs
StatePublished - Feb 26 2023
Event17th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2023 - Warsaw, Poland
Duration: Feb 26 2023Mar 1 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference17th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2023
Country/TerritoryPoland
CityWarsaw
Period2/26/233/1/23

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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