Development of a Prototype Sensory Device as a Substitute for Single Sided Deaf People in Developing Nations
Bibliographic record
Abstract
Hearing loss is the inability to hear sounds ranging from 20 decibels or more in one or both ears. It can affect one or both ears and leads to difficulty in hearing speech or sounds in general. Single-sided deafness or unilateral hearing loss is a very widespread disability. However, most people only see hearing loss as being a binary problem assuming that you either have perfect hearing in both ears or are completely deaf in both ears, and dismiss the other types of hearing loss. Sensory substitution involves remapping the information gathered by one sensory receptor to another. Sensory receptors regardless of the signals they receive or capture, all encode the gathered information as electrochemical signals. This biological property of sensory receptors, coupled with the human brain’s neuroplasticity allows sensory receptors to be substituted, giving rise to new methods of sensory perception. This study aims to develop a sensory device known as a localizer. The localizer detects sound using numerous sound sensors, and feeds the input to the microcontrollers which then use the input to control the eccentric mass motor by implementing various motor drivers. The results gotten from this prototype device shows great improvement in the ability of a single-sided deaf person to localize sound.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".