Extending a mobile device's interaction space through body-centric interaction
Bibliographic record
Abstract
Modern mobile devices rely on the screen as a primary input modality. Yet the small screen real-estate limits interaction possibilities, motivating researchers to explore alternate input techniques. Within this arena, our goal is to develop Body-Centric Interaction with Mobile Devices: a class of input techniques that allow a person to position and orient her mobile device to navigate and manipulate digital content anchored in the space on and around the body. To achieve this goal, we explore such interaction in a bottom-up path of prototypes and implementations. From our experiences, as well as by examining related work, we discuss and present three recurring themes that characterize how these interactions can be realized. We illustrate how these themes can inform the design of Body-Centric Interactions by applying them to the design of a novel mobile browser application. Overall, we contribute a class of mobile input techniques where interactions are extended beyond the small screen, and are instead driven by a person's movement of the device on and around the body.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".