University of Wales Trinity Saint David
Bio-rhythms / Digi-rhythms: Synthesising the Digitally Mediated Body Through Performative Methodologies
Abstract
dc:description.abstractThis research focuses on contemporary practices of digital self-tracking, popularised through the rise in biometric devices, which enable subjects to track their health in terms of biometric data and movements such as the Quantified Self which provide a platform for individuals to share their health data and self-tracking practices. This research explores how biometric devices enable us to simultaneously selfproduce our identities and allow data versions of ourselves to be ‘captured’ by bigdata analytics, which subsequently inform the health parameters of a biopolitical discourse. As digital devices increasingly permeate our lives, the ‘biorhythms’ of embodied experience are arguably given less cultural significance. This research proposes the development of a subjective negotiation of the body, through performative and embodied aesthetic research methodologies, which will develop a theoretical framework for how we might better ‘speak’ our bodies in a post-digital context. Using the theory of Rhythmanalysis (2004), developed by Henri Lefebvre, rhythm will be adopted as a metaphor for re-thinking our interrelation with digital interfaces, beyond the limiting parameters of a dualistic understanding of the biological body and the digitally-mediated body. This research proposes a ‘rhythm-analytical’ approach, a space between the sensory body (bio-rhythm) and its mediation through the digital (digi-rhythm), as a methodology to synthesise bio/digital polarities.
Degree
thesis:*- Name dc:type.qualificationname
- phd
- Level dc:type.qualificationlevel
- doctoral
- Grantor dc:publisher.institution
- University of Wales Trinity Saint David
- Year dc:date.issued
- 2021
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Hughes, Kathryn Lawson
Subjects
dc:subject × 1Identifiers
dc:identifier.*- Dc Identifier Grantnumber
- UWTSD
- OAI identifier oai:identifier
- oai:repository.uwtsd.ac.uk:1650