Investigating the Effects of Intensity and Frequency on Vibrotactile Spatial Acuity
Bibliographic record
Abstract
Vibrotactile devices are commonly used in applications for sensory substitution or to provide feedback in virtual reality. An important aspect of vibrotactile perception is spatial acuity, which determines the resolutions of vibrotactile displays on the skin. However, the complex vibration characteristics of vibrotactile actuators make it challenging for researchers to reference and compare previous study results. This is because the effects of typical characteristics, such as intensity and frequency, are not well understood. In this study, we investigated the effects of intensity and frequency on vibrotactile spatial acuity. Using Linear Resonant Actuators (LRAs), we conducted relative point localization experiments to measure spatial acuity under different conditions. In the first experiment, we found that intensity had a significant effect on spatial acuity, with higher intensity leading to better acuity. In the second experiment, using a carefully designed intensity calibration procedure, we did not find a significant effect of frequency on spatial acuity. These findings provide a better understanding of vibrotactile spatial acuity, allow for comparisons to previous research, and provide insights into the design of future tactile devices.
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".