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Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
How Algorithmic Technologies 'Constitute' the Older Body: A Study of Fall-Detection Wearables
Geoffrey Mead1, Barbara B Neves1,2, Alex Broom1
1Sydney Centre for Healthy Societies, School of Social and Political Sciences, The University of Sydney, Sydney, New South Wales, Australia.
None:
The cultural politics of the 'problematic' ageing body have led to a search for solutions in the form of algorithmic technologies. In this article, we look at one problem associated with the ageing body-unintentional falls-and one proposed algorithmic intervention: wearable fall-detection technology. In dialogue with sociologists concerned with the cultural politics of the older body, we aim to understand what contribution this fledgling technology makes to how the older body is 'constituted'. To do this, we examine a sample of datasets containing measurements of individuals' movements and falls (which researchers have made available to train algorithms for use in fall-detection wearables). In contrast to existing attempts to grasp how older users are scripted into technology, which focus on explicit ideas about them, we trace how individual subjects are formatted in these datasets. We find that these individuals become fragmented in the data, rendered into movements abstracted from the bodies that carry them out and the locations in which they take place. The older body is constituted, then, as a risky, deviant set of movements through space, irreducible to its component parts.
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