The Use of Artificial Intelligence in the Design of an Intelligent Cognitive Orthosis for People with Dementia
Bibliographic record
Abstract
Dementia often reduces a person's ability to perform activities of daily living because he or she becomes confused and cannot remember the sequence of steps to perform. The current solution is to have a caregiver continually supervise and assist the person using verbal reminders or cues. This loss of privacy and increased dependency may cause the affected person to become embarrassed and agitated. We propose that this situation might be improved by using a computerized device that monitors progress and provides the reminders needed. The COACH is a first prototype of such a device. It uses artificial intelligence to observe a user, learn from his or her actions, and issue prerecorded cues of varying detail. The device was developed using a personal computer and a video camera that unobtrusively tracked the user. Preliminary testing with subjects who simulated confused behavior as they washed their hands showed that the device was performing its functions with an efficacy of approximately 95%. More extensive clinical testing and evaluation has begun, and the results will be reported in future publications.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".