Towards a physiological signal-based access solution for a non-verbal adolescent with severe and multiple disabilities
Bibliographic record
Abstract
OBJECTIVE: To find physiologically arousing stimuli and labile physiological channels in a non-verbal adolescent with severe and multiple congenital disabilities, who did not have a reliable means of communication. METHODS: The client was repeatedly presented with visual and audiovisual stimuli, representing variations of six contextual factors over three sessions in a one month period. For each stimulus, reactions were detected in the client's four peripheral autonomic nervous system signals using a rule-based classification algorithm. RESULTS: During the presentation of audiovisual stimuli, the number of physiological reactions significantly differed from that observed in baseline (χ(2) = 3.93, p = 0.0476). Aural stimuli articulated in an unfamiliar voice, and aural stimuli containing anticipatory patterns were also physiologically arousing. Fingertip temperature was the client's most labile physiological signal. CONCLUSIONS: The results of this case study suggest that physiological data may complement caregiver acumen in deciphering the reactions of non-verbal clients with severe and multiple disabilities.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".