arXiv subjects

Susanne Boll

Publications and source records attributed to Susanne Boll.

3 recordsLinked to original sources

arXiv2026

Grand Challenges around Designing Computers' Control Over Our Bodies

Advances in emerging technologies, such as on-body mechanical actuators and electrical muscle stimulation, have allowed computers to take control over our bodies. This presents opportunities as well as challenges, raising fundamental questions about agency and the role of our bodies when interacting with technology. To advance this research field as a whole, we brought together expert perspectives in a week-long seminar to articulate the grand challenges that should be tackled when it comes to the design of computers' control over our bodies. These grand challenges span technical, design, user, and ethical aspects. By articulating these grand challenges, we aim to begin initiating a research agenda that positions bodily control not only as a technical feature but as a central, experiential, and ethical concern for future human-computer interaction endeavors.

cs.HC↗

arXiv2019

PrivacEye: Privacy-Preserving Head-Mounted Eye Tracking Using Egocentric Scene Image and Eye Movement Features

Eyewear devices, such as augmented reality displays, increasingly integrate eye tracking but the first-person camera required to map a user's gaze to the visual scene can pose a significant threat to user and bystander privacy. We present PrivacEye, a method to detect privacy-sensitive everyday situations and automatically enable and disable the eye tracker's first-person camera using a mechanical shutter. To close the shutter in privacy-sensitive situations, the method uses a deep representation of the first-person video combined with rich features that encode users' eye movements. To open the shutter without visual input, PrivacEye detects changes in users' eye movements alone to gauge changes in the "privacy level" of the current situation. We evaluate our method on a first-person video dataset recorded in daily life situations of 17 participants, annotated by themselves for privacy sensitivity, and show that our method is effective in preserving privacy in this challenging setting.

cs.HC↗

arXiv2016

VapeTracker: Tracking Vapor Consumption to Help E-cigarette Users Quit

Despite current controversy over e-cigarettes as a smoking cessation aid, we present early work based on a web survey (N=249) that shows that some e-cigarette users (46.2%) want to quit altogether, and that behavioral feedback that can be tracked can fulfill that purpose. Based on our survey findings, we designed VapeTracker, an early prototype that can attach to any e-cigarette device to track vaping activity. We discuss our future research on vaping cessation, addressing how to improve our VapeTracker prototype, ambient feedback mechanisms, and the future inclusion of behavior change models to support quitting e-cigarettes.

cs.HC↗