TACTILE NAVIGATION: AN ADDITIONAL PROCESSING CHANNEL FOR ENVIRONMENTS OF HIGH SENSORY LOAD
Bibliographic record
Abstract
Persons with visual impairments often rely on navigational electronic aids, which typically employ speech commands for guidance through novel routes. However, navigational speech commands may interfere with the perception of acoustically rich environmental information, resulting in potentially detrimental effects. We investigated the sense of touch as a means to convey navigational commands instead. The somatotopic representation of the body surface within the central nervous system makes spatial information intuitive to our skin, suggesting that the tactile channel should be equivalent to, if not better than, the auditory channel at processing directional commands. Additionally, based on Wickens’ Multiple resource theory, the tactile channel should mitigate the sensory load in the auditory channel in travelers with visual impairments. We tested the ability of blind users to process directional commands conveyed via a tactile navigational belt. 14 blind participants were tested with the tactile belt under conditions of either low or high acoustic sensory load, simulating different outdoor environments. For comparison, the same participants were tested also with a conventional auditory device. Consistent with previous studies, we found navigation with the tactile belt to be less efficient than navigation with the auditory aid in the absence of environmental sounds. However, we found also – for the first time, to our knowledge – that tactile performance was less compromised under conditions of high acoustic sensory load. These results will help to inform the further investigation and development of tactile displays to benefit blind travelers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".