The performance of indirect foot pointing using discrete taps and kicks while standing
Why this work is in the frame
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Bibliographic record
Abstract
We investigate the performance of indirect foot pointing while standing using discrete taps and kicks. Two experiments show that left and right feet perform at similar levels, there is little difference in selection time across target configurations or directions, but targets with an angular size under 22.5° or radial size under 5cm should be avoided due to high error rates. There is a detectable advantage to tapping compared to kicking, but little practical difference. Although cursor feedback is optimal, we show that eyes-free foot pointing achieves an error rate of 27% for 45° angular targets. We translate our results into ten design guidelines and we illustrate their application by designing foot interaction techniques to control desktop applications at a standing desk.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it