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Record W1994227203 · doi:10.1097/wnr.0b013e3283462def

Navigation with a sensory substitution device in congenitally blind individuals

2011· article· en· W1994227203 on OpenAlexafffund
Daniel‐Robert Chebat, F. Schneider, Ron Kupers, Maurice Ptito

Bibliographic record

VenueNeuroreport · 2011
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsSensory substitutionSensory systemObstacle avoidanceTask (project management)Substitution (logic)TonguePsychologyObstacleComputer scienceAudiologyComputer visionPhysical medicine and rehabilitationCognitive psychologyArtificial intelligenceMedicineEngineering

Abstract

fetched live from OpenAlex

Vision allows for obstacle detection and avoidance. The compensatory mechanisms involved in maintaining these functions in blind people using their remaining intact senses are poorly understood. We investigated the ability of congenitally blind participants to detect and avoid obstacles using the tongue display unit, a sensory substitution device that uses the tongue as a portal to the brain. We found that congenitally blind were better than sighted control participants in detecting and avoiding obstacles using the tongue display unit. Obstacles size and avoidance strategy had a significant effect on performance: large obstacles were better detected than small ones and step-around obstacles were better avoided than step-over ones. These data extend our earlier findings that when using a sensory substitution device, blind participants outperform sighted controls not only in a virtual navigation task but also during effective navigation within a human-sized obstacle course.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.122
GPT teacher head0.307
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations134
Published2011
Admission routes2
Has abstractyes

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