A real-world deployment of the COACH prompting system
Bibliographic record
Abstract
The loss of cognition associated with dementia affects an individual's ability to participate in even the most fundamental activities of daily living (ADL). Assistive technology for cognition (ATC) has shown potential to support ADL completion, but few devices have undergone real-world deployments. The COACH is an existing ATC that has been shown in supervised trials to support older adults with dementia through the ADL of hand washing. This paper presents the results of a study of the COACH in a long-term, real-world, community-based deployment. The COACH was installed in a washroom at the Toronto Memory Program. The COACH was configured to run in an unsupervised state, interacting with users when they were not progressing through the task. Video was collected from an overhead camera, and was manually annotated to determine the system's capabilities. The trials were conducted from February to May, 2012. Twenty participants contributed forty-one hand washing trials. Results suggest that the COACH was able to identify completed task steps with 46.6% accuracy and the participants' true performance with 54.9% accuracy. This study clarifies the need for more robust, accurate and generalized user tracking, including the use of three-dimensional tracking, gesture, grip and rotation detection.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".