The impact of movement sonification on haptic perception changes with aging
Bibliographic record
Abstract
Combining multisensory sources is crucial to interact with our environment, especially for older people who are facing sensory declines. Here, we examined the influence of textured sounds on haptic exploration of artificial textures in healthy younger and older adults by combining a tactile device (ultrasonic display) with synthetized textured sounds. Participants had to discriminate simulated textures with their right index while they were distracted by three disturbing, more or less textured sounds. These sounds were presented as a real-time auditory feedback based on finger movement sonification and thus gave the sensation that the sounds were produced by the haptic exploration. Finger movement velocity increased across both groups in presence of textured sounds (Rubbing or Squeaking) compared to a non-textured (Neutral) sound. While young adults had the same discrimination threshold, regardless of the sound added, the older adults were more disturbed by the presence of the textured sounds with respect to the Neutral sound. Overall, these findings suggest that irrelevant auditory information was taken into account by all participants, but was appropriately segregated from tactile information by young adults. Older adults failed to segregate auditory information, supporting the hypothesis of general facilitation of multisensory integration with aging.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".