Flytrap Hand: Towards Understanding Dark Patterns of Physical Augmentation via Electrical Muscle Stimulation

Date

2025

Authors

Liu, S.
Ens, B.
Semertzidis, N.A.
Lee, G.A.
Mueller, F.
Elvitigala, D.S.

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Conference paper

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Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2025, pp.913-1-913-2

Statement of Responsibility

Siyi Liu, Barrett Ens, Nathan Arthur Semertzidis, Gun A. Lee, Florian, Floyd, Mueller, Don Samitha Elvitigala

Conference Name

CHI Conference on Human Factors in Computing Systems (CHI EA) (26 Apr 2025 - 1 May 2025 : Japan, Yokohama)

Abstract

Physical augmentation offers opportunities to enhance human abilities, yet these systems can also embed dark patterns that deceive users in ways that are against their best interests. To explore these dark patterns, we developed Flytrap Hand, a system that employs electrical muscle stimulation to automate grasping and releasing actions. While the system enhances grasping speed and reduces physical effort, it also exposes dark patterns in physical augmentation, such as manipulating users through involuntary hand movements and imposing forced control, which diminishes user agency. Ultimately, we hope that our work can deepen the understanding of dark patterns and support practitioners in mitigating these issues within physical augmentation technologies.

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© 2025 Copyright held by the owner/author(s). Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.

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