Body Maps: A Generative Tool for Soma-based DesignShow others and affiliations
2022 (English)In: ACM International Conference Proceeding Series, Association for Computing Machinery , 2022, article id 3502262Conference paper, Published paper (Refereed)
Abstract [en]
Body maps are visual documents, where somatic experiences can be drawn onto a graphical representation of an outline of the human body. They hold the ability to capture complex and non-explicit emotions and somatic felt sensations, elaborating narratives that cannot be simply spoken. We present an illustrative example of "how-to"complete a body map, together with four case studies that provide examples of using body maps in design research. We identify five uses of body maps as generative tools for soma-based design, ranging from sampling bodily experience, heightening bodily self-awareness, understanding changing bodily experience over time, identifying patterns of bodily experience, and transferring somatic experiential qualities into physical designs. The different requirements for scaffolding the use of body maps in user-centred design versus first-person autobiographical design research are discussed. We provide this Pictorial as a resource for designers and researchers who wish to integrate body maps into their practice. © 2022 Owner/Author.
Place, publisher, year, edition, pages
Association for Computing Machinery , 2022. article id 3502262
Keywords [en]
Data visualization, User centered design, Case-studies, Design research, Experiential qualities, First person, Generative tools, Graphical representations, Human bodies, Physical design, Self awareness, Scaffolds
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:ri:diva-58774DOI: 10.1145/3490149.3502262Scopus ID: 2-s2.0-85124985557ISBN: 9781450391474 (print)OAI: oai:DiVA.org:ri-58774DiVA, id: diva2:1642099
Conference
16th International Conference on Tangible, Embedded, and Embodied Interaction, TEI 2022, 13 February 2022 through 16 February 2022
Note
Funding details: Natural Sciences and Engineering Research Council of Canada, NSERC, 2017-06300, 2017-507935; Funding text 1: This work was supported and funded by the National Sciences and Engineering Research Council of Canada (NSERC) through a Discovery grant (2017-06300) and a Discovery Accelerator Supplement (2017-507935).
2022-03-032022-03-032025-09-23Bibliographically approved