Eyelid gestures for people with motor impairments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although eye-based interactions can be beneficial for people with motor impairments, they often rely on clunky or specialized equipment (e.g., stationary eye-trackers) and focus primarily on gaze and blinks. However, two eyelids can open and close in different orders and for different duration to form rich eyelid gestures. We take a first step to design, detect, and evaluate a set of eyelid gestures for people with motor impairments on mobile devices. We present an algorithm to detect nine eyelid gestures on smartphones in real time and evaluate it with 12 able-bodied people and 4 people with severe motor impairments in two studies. The results of the study with people with motor-impairments show that the algorithm can detect the gestures with .76 and .69 overall accuracy in user-dependent and user-independent evaluations. Furthermore, we design and evaluate a gesture mapping scheme for people with motor impairments to navigate mobile applications only using eyelid gestures. Finally, we discuss considerations for designing and using eyelid gestures for people with motor impairments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.018 | 0.010 |
| 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